{ "results": [ { "id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "title": "Founding Head of Product", "employer_name": "Clearly AI", "employer_slug": "clearly-ai", "location_text": "United States | Remote | Seattle", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/clearly-ai/8b9c717e-2e9e-4958-afa2-0e3046a146c2", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Founding Head of Product United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. We need a founding Product Manager who will own product the way a founder does. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS We're hiring a Head of Product to own Clearly AI's roadmap end-to-end, working with our founders to align product strategy against many competing needs from our enterprise customers and set the long-term vision. You'll lead design, discovery, experimentation, and delivery across a repeatable product lifecycle that", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "product", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.5f1bf31e085d0f699d", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding Head of Product United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. We need a founding Product Manager who will own product the way a founder does. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS We're hiring a Head of Product to own Clearly AI's roadmap end-to-end, working with our founders to align product strategy against many competing needs from our enterprise customers and set the long-term vision. You'll lead design, discovery, experimentation, and delivery across a repeatable product lifecycle that", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:2d9cadf9c4a2f7c464b68b7b9c2bf5a0:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.f6901f4122de2427a2", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding Head of Product United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. We need a founding Product Manager who will own product the way a founder does. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS We're hiring a Head of Product to own Clearly AI's roadmap end-to-end, working with our founders to align product strategy against many competing needs from our enterprise customers and set the long-term vision. You'll lead design, discovery, experimentation, and delivery across a repeatable product lifecycle that", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:2d9cadf9c4a2f7c464b68b7b9c2bf5a0:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.02e29ae7baa27fc92a", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:2d9cadf9c4a2f7c464b68b7b9c2bf5a0:employer:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.9ddd46f2f070b836dd", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:2d9cadf9c4a2f7c464b68b7b9c2bf5a0:employer:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.2d53ea46e5bfc52f1c", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:6e8a3a40103f66b894af499f", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.407775a2c655a56f2f", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.fa46daad94c38e31c6", "query_id": "gq_027d2641909897d49713", "job_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/8b9c717e-2e9e-4958-afa2-0e3046a146c2", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/8b9c717e-2e9e-4958-afa2-0e3046a146c2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/8b9c717e-2e9e-4958-afa2-0e3046a146c2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/8b9c717e-2e9e-4958-afa2-0e3046a146c2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "4f1c1848ab82052577e9d4ae4e4de869", "title": "Technical Customer Support Engineer - Security", "employer_name": "Clearly AI", "employer_slug": "clearly-ai", "location_text": "United States | Remote | Seattle", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/clearly-ai/f5914e0c-b67e-4eaa-9bc7-a62905e0050d", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Technical Customer Support Engineer - Security United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. Our customers run security-critical workflows inside complex enterprise environments, and when something breaks they expect an answer that actually fixes it, not a status page. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS Our customers are security practitioners at Fortune 500s. They deploy Clearly AI alongside Jira, ServiceNow, Confluence, and GitHub, and they push the product hard in environments where stakes are real. When a review stalls,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "customer_success", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.58a0b2806a39c4b47d", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Customer Support Engineer - Security United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. Our customers run security-critical workflows inside complex enterprise environments, and when something breaks they expect an answer that actually fixes it, not a status page. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS Our customers are security practitioners at Fortune 500s. They deploy Clearly AI alongside Jira, ServiceNow, Confluence, and GitHub, and they push the product hard in environments where stakes are real. When a review stalls,", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:4f1c1848ab82052577e9d4ae4e4de869:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.ee2721450942a2c384", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Technical Customer Support Engineer - Security United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. Our customers run security-critical workflows inside complex enterprise environments, and when something breaks they expect an answer that actually fixes it, not a status page. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS Our customers are security practitioners at Fortune 500s. They deploy Clearly AI alongside Jira, ServiceNow, Confluence, and GitHub, and they push the product hard in environments where stakes are real. When a review stalls,", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:4f1c1848ab82052577e9d4ae4e4de869:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.5b7241ae6d49953415", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:4f1c1848ab82052577e9d4ae4e4de869:employer:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a36b9126585dd36bf6", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:4f1c1848ab82052577e9d4ae4e4de869:employer:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.49a7e659807dc1427b", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:636876da55f958f464df19c7", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.4d0183d23a32ba79b5", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.83fe848f64dae1a962", "query_id": "gq_027d2641909897d49713", "job_id": "4f1c1848ab82052577e9d4ae4e4de869", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/f5914e0c-b67e-4eaa-9bc7-a62905e0050d", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/f5914e0c-b67e-4eaa-9bc7-a62905e0050d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/f5914e0c-b67e-4eaa-9bc7-a62905e0050d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/f5914e0c-b67e-4eaa-9bc7-a62905e0050d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "562947d0029ba29614cc23b7b5ad7239", "title": "Sr Software Engineer", "employer_name": "Clearly AI", "employer_slug": "clearly-ai", "location_text": "United States | Remote | Seattle", "country": "US", "employment_type": "full_time", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/clearly-ai/b5cc8402-756a-4bb9-af7c-57f38724e804", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr Software Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates security and privacy reviews with AI. We built the product we wish we had after performing hundreds of reviews at Amazon and Moveworks, and today our users complete reviews in minutes instead of days. Clearly AI helps engineering teams ship faster by automating security and privacy reviews. Companies like Rivian, HID Global, and Affirm use Clearly AI to cut review times from weeks to minutes. We're building a new kind of AI workspace designed to help security, privacy, and compliance experts meet high standards in regulated enterprises. We're a fast-growing YC startup with enterprise customers who depend on us to stay secure and compliant without slowing down. As our founding UX/UI design engineer, you'll shape the product experience end-to-end and set the design bar for everything that follows. ROLE DESCRIPTION Full-time, Sr Software Engineer at Clearly AI. You will be responsible for designing and developing enterprise-grade full-stack AI B2B SaaS web apps. Given the size and stage of our startup, you will take responsibility over significant portions of the product. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. QUALIFICATIONS - 5-7+ years of professional experience developing software. - Willingness to work directly with users and prioritize their needs over our internal dev experience. - Strong proficiency in Typescript, NextJS, modern", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 7, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b046a4e634f5620288", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr Software Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates security and privacy reviews with AI. We built the product we wish we had after performing hundreds of reviews at Amazon and Moveworks, and today our users complete reviews in minutes instead of days. Clearly AI helps engineering teams ship faster by automating security and privacy reviews. Companies like Rivian, HID Global, and Affirm use Clearly AI to cut review times from weeks to minutes. We're building a new kind of AI workspace designed to help security, privacy, and compliance experts meet high standards in regulated enterprises. We're a fast-growing YC startup with enterprise customers who depend on us to stay secure and compliant without slowing down. As our founding UX/UI design engineer, you'll shape the product experience end-to-end and set the design bar for everything that follows. ROLE DESCRIPTION Full-time, Sr Software Engineer at Clearly AI. You will be responsible for designing and developing enterprise-grade full-stack AI B2B SaaS web apps. Given the size and stage of our startup, you will take responsibility over significant portions of the product. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. QUALIFICATIONS - 5-7+ years of professional experience developing software. - Willingness to work directly with users and prioritize their needs over our internal dev experience. - Strong proficiency in Typescript, NextJS, modern", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:562947d0029ba29614cc23b7b5ad7239:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d5565e5423559a1493", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr Software Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates security and privacy reviews with AI. We built the product we wish we had after performing hundreds of reviews at Amazon and Moveworks, and today our users complete reviews in minutes instead of days. Clearly AI helps engineering teams ship faster by automating security and privacy reviews. Companies like Rivian, HID Global, and Affirm use Clearly AI to cut review times from weeks to minutes. We're building a new kind of AI workspace designed to help security, privacy, and compliance experts meet high standards in regulated enterprises. We're a fast-growing YC startup with enterprise customers who depend on us to stay secure and compliant without slowing down. As our founding UX/UI design engineer, you'll shape the product experience end-to-end and set the design bar for everything that follows. ROLE DESCRIPTION Full-time, Sr Software Engineer at Clearly AI. You will be responsible for designing and developing enterprise-grade full-stack AI B2B SaaS web apps. Given the size and stage of our startup, you will take responsibility over significant portions of the product. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. QUALIFICATIONS - 5-7+ years of professional experience developing software. - Willingness to work directly with users and prioritize their needs over our internal dev experience. - Strong proficiency in Typescript, NextJS, modern", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:562947d0029ba29614cc23b7b5ad7239:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.9e8ba0294f8f158fa1", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:562947d0029ba29614cc23b7b5ad7239:employer:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.d11abb4b795b6014b7", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:562947d0029ba29614cc23b7b5ad7239:employer:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.d54ab5c7ce9dbcbf42", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:74968a71b6ad193be7895902", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.a839500088428cc362", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.f4850a909d9deab338", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.0f1312dfc13ef57da2", "query_id": "gq_027d2641909897d49713", "job_id": "562947d0029ba29614cc23b7b5ad7239", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "engineering", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:562947d0029ba29614cc23b7b5ad7239:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b5cc8402-756a-4bb9-af7c-57f38724e804", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b5cc8402-756a-4bb9-af7c-57f38724e804", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b5cc8402-756a-4bb9-af7c-57f38724e804", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b5cc8402-756a-4bb9-af7c-57f38724e804", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "7dac22dc8b07ff02d30bd36f171a5105", "title": "Founding GTM Engineer", "employer_name": "Clearly AI", "employer_slug": "clearly-ai", "location_text": "United States | Remote | Seattle", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/clearly-ai/d12ec43e-397e-496f-a0d4-ac23783bfb68", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Founding GTM Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS We've proven we can land and expand inside some of the world's most demanding security organizations. Now we need to build the machine that scales it. This is not a RevOps generalist role or a traditional marketing ops hire. We're looking for someone who thinks like an engineer and operates like a strategist - someone who can design and build an AI-native GTM engine from scratch, then draw the insights that tell us what's actually working. The right person has built real systems, written real code, and has strong opinions about how AI changes what's possible in go-to-market. You'll be the first person in this function, with", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "marketing", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.8564581650d3a52ad5", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding GTM Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS We've proven we can land and expand inside some of the world's most demanding security organizations. Now we need to build the machine that scales it. This is not a RevOps generalist role or a traditional marketing ops hire. We're looking for someone who thinks like an engineer and operates like a strategist - someone who can design and build an AI-native GTM engine from scratch, then draw the insights that tell us what's actually working. The right person has built real systems, written real code, and has strong opinions about how AI changes what's possible in go-to-market. You'll be the first person in this function, with", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:7dac22dc8b07ff02d30bd36f171a5105:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b6580154ee4cb1f1b3", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding GTM Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS We've proven we can land and expand inside some of the world's most demanding security organizations. Now we need to build the machine that scales it. This is not a RevOps generalist role or a traditional marketing ops hire. We're looking for someone who thinks like an engineer and operates like a strategist - someone who can design and build an AI-native GTM engine from scratch, then draw the insights that tell us what's actually working. The right person has built real systems, written real code, and has strong opinions about how AI changes what's possible in go-to-market. You'll be the first person in this function, with", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:7dac22dc8b07ff02d30bd36f171a5105:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.5a12171b908cb2b1df", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:7dac22dc8b07ff02d30bd36f171a5105:employer:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.e0db82f9fc2aa863f2", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:7dac22dc8b07ff02d30bd36f171a5105:employer:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.1c83a4fdf8571f7108", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:64f910c773ad976549cd8116", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.3c2ecc3be0bf2b2d95", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.e843f508767331d789", "query_id": "gq_027d2641909897d49713", "job_id": "7dac22dc8b07ff02d30bd36f171a5105", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/d12ec43e-397e-496f-a0d4-ac23783bfb68", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/d12ec43e-397e-496f-a0d4-ac23783bfb68", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/d12ec43e-397e-496f-a0d4-ac23783bfb68", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/d12ec43e-397e-496f-a0d4-ac23783bfb68", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "addb6ece698d4434b71154d8a0bbb04b", "title": "Forward Deployed Security Engineer", "employer_name": "Clearly AI", "employer_slug": "clearly-ai", "location_text": "United States | Remote | Seattle", "country": "US", "employment_type": "contract", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/clearly-ai/b17dc38d-1da9-4ac3-aaf9-196aa93941b1", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Forward Deployed Security Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS Our customers are Fortune 500s and global brands operating inside complex, highly regulated security environments. They need someone who can: - Understand real security workflows across threat modeling, privacy, and vendor risk - Integrate Clearly AI into those workflows alongside Jira, ServiceNow, Confluence, and GitHub - Drive disciplined implementation from contract to production - Translate deployment friction into shipped product improvements", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.04ca3fde2765708f78", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Forward Deployed Security Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS Our customers are Fortune 500s and global brands operating inside complex, highly regulated security environments. They need someone who can: - Understand real security workflows across threat modeling, privacy, and vendor risk - Integrate Clearly AI into those workflows alongside Jira, ServiceNow, Confluence, and GitHub - Drive disciplined implementation from contract to production - Translate deployment friction into shipped product improvements", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:addb6ece698d4434b71154d8a0bbb04b:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.ca9ce57e56b465708b", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Forward Deployed Security Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates the most painful bottleneck in the enterprise: security and privacy reviews. We help security teams complete high-quality threat models, privacy impact assessments, and vendor risk evaluations in minutes instead of weeks. We're live with Fortune 500s and global brands including Rivian, Ericsson, HID Global, Affirm, Webflow, and Okta. We've reviewed thousands of security-critical products, from badge scanners to stablecoin platforms to autonomous driving features. Backed by Y Combinator, Basis Set Ventures, Crosspoint Capital, Argon Ventures, and Ritual Capital. Selected as a Top 10 Finalist for the RSAC 2026 Innovation Sandbox Contest. Advised by former CISOs of Amplitude and OKX, the former CEO of Reddit, and the former CPO of Brex. We are early. We are deeply technical. We are building alongside real practitioners, and we want a real practitioner who loves working with customers to help. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. WHY THIS ROLE EXISTS Our customers are Fortune 500s and global brands operating inside complex, highly regulated security environments. They need someone who can: - Understand real security workflows across threat modeling, privacy, and vendor risk - Integrate Clearly AI into those workflows alongside Jira, ServiceNow, Confluence, and GitHub - Drive disciplined implementation from contract to production - Translate deployment friction into shipped product improvements", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:addb6ece698d4434b71154d8a0bbb04b:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.583cb02eb07a674e4a", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:addb6ece698d4434b71154d8a0bbb04b:employer:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.ceed245ac2533ea1f2", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:addb6ece698d4434b71154d8a0bbb04b:employer:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.d9dfe463afcbf9fee3", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:adb66041640c52c2443614b1", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.7702108301bf7c0859", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.f844cad3a40d6638bf", "query_id": "gq_027d2641909897d49713", "job_id": "addb6ece698d4434b71154d8a0bbb04b", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b17dc38d-1da9-4ac3-aaf9-196aa93941b1", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b17dc38d-1da9-4ac3-aaf9-196aa93941b1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b17dc38d-1da9-4ac3-aaf9-196aa93941b1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/b17dc38d-1da9-4ac3-aaf9-196aa93941b1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "title": "Founding UX/UI Design Engineer", "employer_name": "Clearly AI", "employer_slug": "clearly-ai", "location_text": "United States | Remote | Seattle", "country": "US", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 6, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.ashbyhq.com/clearly-ai/6d15aab7-bba2-4acf-a76d-37657e81981d", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Founding UX/UI Design Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates security and privacy reviews with AI. We built the product we wish we had after performing hundreds of reviews at Amazon and Moveworks, and today our users complete reviews in minutes instead of days. Clearly AI helps engineering teams ship faster by automating security and privacy reviews. Companies like Rivian, HID Global, and Affirm use Clearly AI to cut review times from weeks to minutes. We're building a new kind of AI workspace designed to help security, privacy, and compliance experts meet high standards in regulated enterprises. We're a fast-growing YC startup with enterprise customers who depend on us to stay secure and compliant without slowing down. As our founding UX/UI design engineer, you'll shape the product experience end-to-end and set the design bar for everything that follows. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. THE ROLE Everyone talks about 10x engineers but the real risk for most companies is not whether you can build it, it's if you're building the right thing. We want designers that can distill why a user is adopting and then prototype the most clear version of that insight. Our users want to work with you. Our users are subject matter experts at global enterprises. Our users have high standards and demand the", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 51, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "design", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "seed", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.65c5133e8fd6a28dd5", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding UX/UI Design Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates security and privacy reviews with AI. We built the product we wish we had after performing hundreds of reviews at Amazon and Moveworks, and today our users complete reviews in minutes instead of days. Clearly AI helps engineering teams ship faster by automating security and privacy reviews. Companies like Rivian, HID Global, and Affirm use Clearly AI to cut review times from weeks to minutes. We're building a new kind of AI workspace designed to help security, privacy, and compliance experts meet high standards in regulated enterprises. We're a fast-growing YC startup with enterprise customers who depend on us to stay secure and compliant without slowing down. As our founding UX/UI design engineer, you'll shape the product experience end-to-end and set the design bar for everything that follows. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. THE ROLE Everyone talks about 10x engineers but the real risk for most companies is not whether you can build it, it's if you're building the right thing. We want designers that can distill why a user is adopting and then prototype the most clear version of that insight. Our users want to work with you. Our users are subject matter experts at global enterprises. Our users have high standards and demand the", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e48e0a3b26b9943e4e10f3a9e4dfcd87:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.98c3308db8c76ebef7", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Founding UX/UI Design Engineer United States | Remote | Seattle ABOUT CLEARLY AI Clearly AI automates security and privacy reviews with AI. We built the product we wish we had after performing hundreds of reviews at Amazon and Moveworks, and today our users complete reviews in minutes instead of days. Clearly AI helps engineering teams ship faster by automating security and privacy reviews. Companies like Rivian, HID Global, and Affirm use Clearly AI to cut review times from weeks to minutes. We're building a new kind of AI workspace designed to help security, privacy, and compliance experts meet high standards in regulated enterprises. We're a fast-growing YC startup with enterprise customers who depend on us to stay secure and compliant without slowing down. As our founding UX/UI design engineer, you'll shape the product experience end-to-end and set the design bar for everything that follows. LOCATION Seattle/SF preferred, remote OK. We meet in person 1-2x per quarter. Applicants must be authorized to work in the United States without the need for visa sponsorship now or in the future. THE ROLE Everyone talks about 10x engineers but the real risk for most companies is not whether you can build it, it's if you're building the right thing. We want designers that can distill why a user is adopting and then prototype the most clear version of that insight. Our users want to work with you. Our users are subject matter experts at global enterprises. Our users have high standards and demand the", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e48e0a3b26b9943e4e10f3a9e4dfcd87:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.08c5646c646fac2826", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e48e0a3b26b9943e4e10f3a9e4dfcd87:employer:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.e17c374b8c44c488f5", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e48e0a3b26b9943e4e10f3a9e4dfcd87:employer:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.employer_name.9ad1da94501d052855", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Employer: semantic match", "tooltip": "Employer provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:ed81b40bf91965267b6954a7", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.093c7b113e2e407c98", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Employer: \"ai\"", "tooltip": "Employer contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.employer_name.79605430c7eadf68a1", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Employer: \"clearly\"", "tooltip": "Employer contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "employer_name", "source_value": "Clearly AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.4da05dfb3a348e4930", "query_id": "gq_027d2641909897d49713", "job_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "design", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e48e0a3b26b9943e4e10f3a9e4dfcd87:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/6d15aab7-bba2-4acf-a76d-37657e81981d", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/6d15aab7-bba2-4acf-a76d-37657e81981d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/6d15aab7-bba2-4acf-a76d-37657e81981d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/clearly-ai/6d15aab7-bba2-4acf-a76d-37657e81981d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "962fe4f9730385011447431106d66715", "title": "Senior AI Engineer", "employer_name": "Quantum Computing", "employer_slug": "quantum-computing", "location_text": "London (hybrid)", "country": "GB", "employment_type": "unknown", "remote_status": "hybrid", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 2, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://jobs.ashbyhq.com/quantum/e42d30b8-6b00-403e-9dcc-3eb313edf54b", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Engineer London (hybrid)", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1758009/000121390026022417/ea0278445-10k_quantum.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1758009/000121390026022417/ea0278445-10k_quantum.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.cf52a96a671474705f", "query_id": "gq_027d2641909897d49713", "job_id": "962fe4f9730385011447431106d66715", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Senior AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:8000b0ec53f1f618a559d7b5", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.99b646eabbd7405b72", "query_id": "gq_027d2641909897d49713", "job_id": "962fe4f9730385011447431106d66715", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Senior AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.ff5c010c5059c3ab12", "query_id": "gq_027d2641909897d49713", "job_id": "962fe4f9730385011447431106d66715", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:962fe4f9730385011447431106d66715:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/quantum/e42d30b8-6b00-403e-9dcc-3eb313edf54b", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1758009/000121390026022417/ea0278445-10k_quantum.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1758009/000121390026022417/ea0278445-10k_quantum.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/quantum/e42d30b8-6b00-403e-9dcc-3eb313edf54b", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.ashbyhq.com/quantum/e42d30b8-6b00-403e-9dcc-3eb313edf54b", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "935b0898508dc89e2f72e49009f4a66f", "title": "Sr. Software Engineer (AI)", "employer_name": "Pendo", "employer_slug": "pendo", "location_text": "New York, NY", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 209000, "salary_max": 235000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 209000, "base_salary_max": 235000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-05-05T18:03:52.000Z", "apply_url": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Sr. Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. - Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. - Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "field": "k401_match", "source": "llm:greenfield:inv_371_postfix", "db_column": "k401_match" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.2ceeac65053d7ef7ad", "query_id": "gq_027d2641909897d49713", "job_id": "935b0898508dc89e2f72e49009f4a66f", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. - Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. - Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:935b0898508dc89e2f72e49009f4a66f:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b782f0c3c5fadda378", "query_id": "gq_027d2641909897d49713", "job_id": "935b0898508dc89e2f72e49009f4a66f", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Sr. Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. - Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. - Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:935b0898508dc89e2f72e49009f4a66f:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.dceb8c555924ad5964", "query_id": "gq_027d2641909897d49713", "job_id": "935b0898508dc89e2f72e49009f4a66f", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Sr. Software Engineer (AI)", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:935b0898508dc89e2f72e49009f4a66f:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.description_excerpt.b572622a3a8d75006a", "query_id": "gq_027d2641909897d49713", "job_id": "935b0898508dc89e2f72e49009f4a66f", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Sr. Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. - Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. - Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:721271c3e4ba63e289487c6f", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.a603b3be4fa9863118", "query_id": "gq_027d2641909897d49713", "job_id": "935b0898508dc89e2f72e49009f4a66f", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Sr. Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. - Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. - Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.b4b38d4e81f4b34490", "query_id": "gq_027d2641909897d49713", "job_id": "935b0898508dc89e2f72e49009f4a66f", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Sr. Software Engineer (AI)", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533495002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "be5956e6d7ff7bb5d9d101bb86947b05", "title": "Staff Software Engineer (AI)", "employer_name": "Pendo", "employer_slug": "pendo", "location_text": "New York, NY", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 245000, "salary_max": 275000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 245000, "base_salary_max": 275000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-05-05T18:04:00.000Z", "apply_url": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Staff Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. - Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. - Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "field": "k401_match", "source": "llm:greenfield:inv_371_postfix", "db_column": "k401_match" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.3eb890d3837e0e6174", "query_id": "gq_027d2641909897d49713", "job_id": "be5956e6d7ff7bb5d9d101bb86947b05", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Staff Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. - Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. - Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:be5956e6d7ff7bb5d9d101bb86947b05:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d17111355896b2dad5", "query_id": "gq_027d2641909897d49713", "job_id": "be5956e6d7ff7bb5d9d101bb86947b05", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Staff Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. - Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. - Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:be5956e6d7ff7bb5d9d101bb86947b05:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.2621bd05a2ca333420", "query_id": "gq_027d2641909897d49713", "job_id": "be5956e6d7ff7bb5d9d101bb86947b05", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Staff Software Engineer (AI)", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:be5956e6d7ff7bb5d9d101bb86947b05:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.description_excerpt.088eeff54e23111cbb", "query_id": "gq_027d2641909897d49713", "job_id": "be5956e6d7ff7bb5d9d101bb86947b05", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Staff Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. - Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. - Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:6aa8898aa4c6d16bcbe91f99", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.7046a2bfc526857d95", "query_id": "gq_027d2641909897d49713", "job_id": "be5956e6d7ff7bb5d9d101bb86947b05", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Staff Software Engineer (AI) New York, NY The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day - Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. - Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. - Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.5a8bd503563641be21", "query_id": "gq_027d2641909897d49713", "job_id": "be5956e6d7ff7bb5d9d101bb86947b05", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Staff Software Engineer (AI)", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "k401_match": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/pendo/jobs/8533499002", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "6bd762860b96b1fc324e69514510ac7b", "title": "Senior AI Research Scientist", "employer_name": "Cerence Inc", "employer_slug": "cerence", "location_text": "Remote - Germany", "country": "DE", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-11T00:00:00.000Z", "apply_url": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior AI Research Scientist Remote - Germany posted: Posted Yesterday", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 48, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.fde2c7a54072b5f8ea", "query_id": "gq_027d2641909897d49713", "job_id": "6bd762860b96b1fc324e69514510ac7b", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Senior AI Research Scientist", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:3a95fa2de3eb70e24e4250bb", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.08c5682f20dcc0eaff", "query_id": "gq_027d2641909897d49713", "job_id": "6bd762860b96b1fc324e69514510ac7b", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Senior AI Research Scientist", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.335bc9e411a47fcaa1", "query_id": "gq_027d2641909897d49713", "job_id": "6bd762860b96b1fc324e69514510ac7b", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:6bd762860b96b1fc324e69514510ac7b:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Senior-AI-Research-Scientist_R0005923", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "e3cf7f0fd074ec5454d1178d48fed01f", "title": "Principal AI Scientist", "employer_name": "Cerence Inc", "employer_slug": "cerence", "location_text": "Remote - Germany", "country": "DE", "employment_type": "unknown", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-11T00:00:00.000Z", "apply_url": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Principal-AI-Scientist_R0005798", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Principal AI Scientist Remote - Germany posted: Posted Yesterday", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 48, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.a335baab5d4608a99f", "query_id": "gq_027d2641909897d49713", "job_id": "e3cf7f0fd074ec5454d1178d48fed01f", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Principal AI Scientist", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:fb80ff74ee152fd9cd7365be", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.5ec55dce02e7442253", "query_id": "gq_027d2641909897d49713", "job_id": "e3cf7f0fd074ec5454d1178d48fed01f", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Principal AI Scientist", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.b63a4e8d76675e1d33", "query_id": "gq_027d2641909897d49713", "job_id": "e3cf7f0fd074ec5454d1178d48fed01f", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e3cf7f0fd074ec5454d1178d48fed01f:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Principal-AI-Scientist_R0005798", "source_values": [ "rule:remote_status" ], "checked_at": null }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1768267/000162828025053372/crnc-20250930.htm" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Principal-AI-Scientist_R0005798", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://cerence.wd5.myworkdayjobs.com/Cerence/job/Remote---Germany/Principal-AI-Scientist_R0005798", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "a33f6668845b5d0d8559c2144d10a952", "title": "Forward Deployed AI Engineer", "employer_name": "Clear", "employer_slug": "clear", "location_text": "New York, NY, United States", "country": "US", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 110000, "salary_max": 160000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "total_comp", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 110000, "base_salary_max": 160000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2026-06-07T17:58:24.000Z", "apply_url": "https://job-boards.greenhouse.io/clear/jobs/7927496", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Forward Deployed AI Engineer New York, NY, United States CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier-physically and digitally. With more than 38 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it's at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. In this role, you will design, build, and deploy AI-powered systems that accelerate AI adoption across CLEAR's internal workflows and customer-facing product experiences. This role will partner directly with Product, Engineering, Data, Security, Legal, Compliance, Operations, and business teams to identify high-impact AI opportunities, rapidly prototype solutions, and productionize reliable, secure, and measurable AI systems. You will own use cases end-to-end, from discovery and evaluation through launch, monitoring, and iteration. What you'll do: Discover, prioritize, and build AI use cases across internal tools, employee workflows, and customer-facing product features Partner with Product, Engineering, Data, Security, Legal, Compliance, and Operations to translate business needs into AI-driven solutions Rapidly prototype AI agents, LLM applications, RAG workflows, automation tools, and product experiences Productionize validated AI use cases with strong evaluation, monitoring, logging, fallback paths, and operational ownership Build reusable patterns for prompt management, retrieval, tool use, evals, guardrails, and human-in-the-loop workflows Implement responsible AI best practices, including privacy, security, model governance, risk review, and customer impact assessment Measure and communicate AI impact across adoption, quality, cost reduction,", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 1, "years_experience_max": 5, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.56208d4d9544416298", "query_id": "gq_027d2641909897d49713", "job_id": "a33f6668845b5d0d8559c2144d10a952", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Forward Deployed AI Engineer New York, NY, United States CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier-physically and digitally. With more than 38 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it's at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. In this role, you will design, build, and deploy AI-powered systems that accelerate AI adoption across CLEAR's internal workflows and customer-facing product experiences. This role will partner directly with Product, Engineering, Data, Security, Legal, Compliance, Operations, and business teams to identify high-impact AI opportunities, rapidly prototype solutions, and productionize reliable, secure, and measurable AI systems. You will own use cases end-to-end, from discovery and evaluation through launch, monitoring, and iteration. What you'll do: Discover, prioritize, and build AI use cases across internal tools, employee workflows, and customer-facing product features Partner with Product, Engineering, Data, Security, Legal, Compliance, and Operations to translate business needs into AI-driven solutions Rapidly prototype AI agents, LLM applications, RAG workflows, automation tools, and product experiences Productionize validated AI use cases with strong evaluation, monitoring, logging, fallback paths, and operational ownership Build reusable patterns for prompt management, retrieval, tool use, evals, guardrails, and human-in-the-loop workflows Implement responsible AI best practices, including privacy, security, model governance, risk review, and customer impact assessment Measure and communicate AI impact across adoption, quality, cost reduction,", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:a33f6668845b5d0d8559c2144d10a952:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.38c675d6b889cc1161", "query_id": "gq_027d2641909897d49713", "job_id": "a33f6668845b5d0d8559c2144d10a952", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Forward Deployed AI Engineer", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:a33f6668845b5d0d8559c2144d10a952:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.1f0f8a7a7de8c56dbc", "query_id": "gq_027d2641909897d49713", "job_id": "a33f6668845b5d0d8559c2144d10a952", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Forward Deployed AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:5bbdac76d745b5f486847774", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.2583953382576a973b", "query_id": "gq_027d2641909897d49713", "job_id": "a33f6668845b5d0d8559c2144d10a952", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Forward Deployed AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/clear/jobs/7927496", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/clear/jobs/7927496", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/clear/jobs/7927496", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/clear/jobs/7927496", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": null }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/clear/jobs/7927496", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.greenhouse.io/clear/jobs/7927496", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "ce4a501fe3bac4a30b83f340bd9ce416", "title": "AI Engineer", "employer_name": "Siemens Energy", "employer_slug": "siemens-energy", "location_text": "Location not specified", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T03:52:15.000Z", "apply_url": "https://jobs.siemens-energy.com/en_US/jobs/FolderDetail?folderId=291491&from=home", "apply_url_verified": false, "ats": "avature", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Energy", "employer_industry_source": "source_sector", "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.d9b8ef44207e2889d5", "query_id": "gq_027d2641909897d49713", "job_id": "ce4a501fe3bac4a30b83f340bd9ce416", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:4a71dda91a0b487ec2f1f77a", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.27ae1afdff365ac3ae", "query_id": "gq_027d2641909897d49713", "job_id": "ce4a501fe3bac4a30b83f340bd9ce416", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.da76920e251509cfc8", "query_id": "gq_027d2641909897d49713", "job_id": "ce4a501fe3bac4a30b83f340bd9ce416", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:ce4a501fe3bac4a30b83f340bd9ce416:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.siemens-energy.com/en_US/jobs/FolderDetail?folderId=291491&from=home", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.siemens-energy.com/en_US/jobs/FolderDetail?folderId=291491&from=home", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "e8650617aebb43bd6d8bf170a6d1088e", "title": "Applied AI Coach", "employer_name": "Salesforce", "employer_slug": "salesforce", "location_text": "Georgia - Atlanta; California - Irvine; New York - New York; California - San Francisco; Colorado - Denver", "country": "US", "employment_type": "internship", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 70070, "salary_max": 119000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 70070, "base_salary_max": 119000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-29T00:00:00.000Z", "apply_url": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "apply_url_verified": false, "ats": "phenom_umbraco", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Applied AI Coach Georgia - Atlanta; California - Irvine; New York - New York; California - San Francisco; Colorado - Denver The Applied AI Coach is part of our new Outcome Acceleration team. Our team works with Agentforce to stay ahead of customer needs and ensure AI delivers real results. In this role, you will own the customer journey from the first sale until their AI deployment is stable and delivering value. You'll bridge the gap between building AI and realizing the business outcomes it was promised to bring. This is a hybrid role, based out of our SMB Hub, requiring an on-site presence 3 days per week. Responsibilities Design and execute success plans to measure whether AI agents are meeting their goals and matching the original business case Run four-week sprints to diagnose and resolve performance issues when AI results are lagging Lead business reviews with customer teams, demonstrating tangible value through outcome data rather than simple usage reports Track AI agent deployment and adoption weekly to ensure stability in production Required Qualifications Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field 1-3 years of work or internship experience in technical roles such as data analytics, engineering, or technical support Proven ability to work directly with customers to solve problems and communicate technical concepts clearly Hands-on experience with prompt engineering, vibe-coding tools, or LLMs Strong analytical skills with the ability to interpret outcome models and prove the value of AI Clear understanding of how AI", "parental_leave_weeks": 26, "non_birth_parent_leave_weeks": 12, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://careers.salesforce.com/en/salesforce-stories/wellbeingbenefits/the-benefits-of-parenthood-how-salesforce-supports-growing-families/", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 93, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_min" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1108524/000110852426000060/crm-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1108524/000110852426000060/crm-20260131.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "industry_vertical": { "field": "industry_vertical", "source": "llm:greenfield:inv_371_postfix", "db_column": "industry_vertical" }, "naics_sector_code": { "field": "naics_sector_code", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_code" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "naics_sector_title": { "field": "naics_sector_title", "source": "llm:greenfield:inv_371_postfix", "db_column": "naics_sector_title" }, "portfolio_required": { "field": "portfolio_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "portfolio_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://careers.salesforce.com/en/salesforce-stories/wellbeingbenefits/the-benefits-of-parenthood-how-salesforce-supports-growing-families/", "db_column": "parental_leave_weeks", "source_url": "https://careers.salesforce.com/en/salesforce-stories/wellbeingbenefits/the-benefits-of-parenthood-how-salesforce-supports-growing-families/" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "llm:greenfield:inv_371_postfix", "db_column": "non_birth_parent_leave_weeks" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 1, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "public-company", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": "Technology", "employer_industry_source": "wikidata_sparql_industry", "employer_size": "5000+", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.0a3396e1b260b79a4d", "query_id": "gq_027d2641909897d49713", "job_id": "e8650617aebb43bd6d8bf170a6d1088e", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description matched \"clearly\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Applied AI Coach Georgia - Atlanta; California - Irvine; New York - New York; California - San Francisco; Colorado - Denver The Applied AI Coach is part of our new Outcome Acceleration team. Our team works with Agentforce to stay ahead of customer needs and ensure AI delivers real results. In this role, you will own the customer journey from the first sale until their AI deployment is stable and delivering value. You'll bridge the gap between building AI and realizing the business outcomes it was promised to bring. This is a hybrid role, based out of our SMB Hub, requiring an on-site presence 3 days per week. Responsibilities Design and execute success plans to measure whether AI agents are meeting their goals and matching the original business case Run four-week sprints to diagnose and resolve performance issues when AI results are lagging Lead business reviews with customer teams, demonstrating tangible value through outcome data rather than simple usage reports Track AI agent deployment and adoption weekly to ensure stability in production Required Qualifications Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field 1-3 years of work or internship experience in technical roles such as data analytics, engineering, or technical support Proven ability to work directly with customers to solve problems and communicate technical concepts clearly Hands-on experience with prompt engineering, vibe-coding tools, or LLMs Strong analytical skills with the ability to interpret outcome models and prove the value of AI Clear understanding of how AI", "matched_input": "clearly", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e8650617aebb43bd6d8bf170a6d1088e:description:clearly", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d3bd1e7d66ab3c5190", "query_id": "gq_027d2641909897d49713", "job_id": "e8650617aebb43bd6d8bf170a6d1088e", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Applied AI Coach Georgia - Atlanta; California - Irvine; New York - New York; California - San Francisco; Colorado - Denver The Applied AI Coach is part of our new Outcome Acceleration team. Our team works with Agentforce to stay ahead of customer needs and ensure AI delivers real results. In this role, you will own the customer journey from the first sale until their AI deployment is stable and delivering value. You'll bridge the gap between building AI and realizing the business outcomes it was promised to bring. This is a hybrid role, based out of our SMB Hub, requiring an on-site presence 3 days per week. Responsibilities Design and execute success plans to measure whether AI agents are meeting their goals and matching the original business case Run four-week sprints to diagnose and resolve performance issues when AI results are lagging Lead business reviews with customer teams, demonstrating tangible value through outcome data rather than simple usage reports Track AI agent deployment and adoption weekly to ensure stability in production Required Qualifications Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field 1-3 years of work or internship experience in technical roles such as data analytics, engineering, or technical support Proven ability to work directly with customers to solve problems and communicate technical concepts clearly Hands-on experience with prompt engineering, vibe-coding tools, or LLMs Strong analytical skills with the ability to interpret outcome models and prove the value of AI Clear understanding of how AI", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e8650617aebb43bd6d8bf170a6d1088e:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.6d4a6c8f386c61fd1e", "query_id": "gq_027d2641909897d49713", "job_id": "e8650617aebb43bd6d8bf170a6d1088e", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Applied AI Coach", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:e8650617aebb43bd6d8bf170a6d1088e:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.description_excerpt.472a46b871964095e9", "query_id": "gq_027d2641909897d49713", "job_id": "e8650617aebb43bd6d8bf170a6d1088e", "signal_type": "query_match", "display_text": "Description: semantic match", "tooltip": "Description provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "description_excerpt", "source_value": "Applied AI Coach Georgia - Atlanta; California - Irvine; New York - New York; California - San Francisco; Colorado - Denver The Applied AI Coach is part of our new Outcome Acceleration team. Our team works with Agentforce to stay ahead of customer needs and ensure AI delivers real results. In this role, you will own the customer journey from the first sale until their AI deployment is stable and delivering value. You'll bridge the gap between building AI and realizing the business outcomes it was promised to bring. This is a hybrid role, based out of our SMB Hub, requiring an on-site presence 3 days per week. Responsibilities Design and execute success plans to measure whether AI agents are meeting their goals and matching the original business case Run four-week sprints to diagnose and resolve performance issues when AI results are lagging Lead business reviews with customer teams, demonstrating tangible value through outcome data rather than simple usage reports Track AI agent deployment and adoption weekly to ensure stability in production Required Qualifications Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field 1-3 years of work or internship experience in technical roles such as data analytics, engineering, or technical support Proven ability to work directly with customers to solve problems and communicate technical concepts clearly Hands-on experience with prompt engineering, vibe-coding tools, or LLMs Strong analytical skills with the ability to interpret outcome models and prove the value of AI Clear understanding of how AI", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:96961276b925aeaaf6e8b1fd", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.b0633d1c2df2b849e9", "query_id": "gq_027d2641909897d49713", "job_id": "e8650617aebb43bd6d8bf170a6d1088e", "signal_type": "query_match", "display_text": "Description: \"clearly\"", "tooltip": "Description contains \"clearly\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Applied AI Coach Georgia - Atlanta; California - Irvine; New York - New York; California - San Francisco; Colorado - Denver The Applied AI Coach is part of our new Outcome Acceleration team. Our team works with Agentforce to stay ahead of customer needs and ensure AI delivers real results. In this role, you will own the customer journey from the first sale until their AI deployment is stable and delivering value. You'll bridge the gap between building AI and realizing the business outcomes it was promised to bring. This is a hybrid role, based out of our SMB Hub, requiring an on-site presence 3 days per week. Responsibilities Design and execute success plans to measure whether AI agents are meeting their goals and matching the original business case Run four-week sprints to diagnose and resolve performance issues when AI results are lagging Lead business reviews with customer teams, demonstrating tangible value through outcome data rather than simple usage reports Track AI agent deployment and adoption weekly to ensure stability in production Required Qualifications Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field 1-3 years of work or internship experience in technical roles such as data analytics, engineering, or technical support Proven ability to work directly with customers to solve problems and communicate technical concepts clearly Hands-on experience with prompt engineering, vibe-coding tools, or LLMs Strong analytical skills with the ability to interpret outcome models and prove the value of AI Clear understanding of how AI", "matched_input": "clearly", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.ee9b508ded77b1d64f", "query_id": "gq_027d2641909897d49713", "job_id": "e8650617aebb43bd6d8bf170a6d1088e", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Applied AI Coach", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1108524/000110852426000060/crm-20260131.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1108524/000110852426000060/crm-20260131.htm" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "https://careers.salesforce.com/en/salesforce-stories/wellbeingbenefits/the-benefits-of-parenthood-how-salesforce-supports-growing-families/" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://careers.salesforce.com/en/jobs/jr339277/applied-ai-coach/", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - Wikidata", "source_label": "Wikidata", "href": null, "source_values": [ "wikidata_sparql_industry" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "cc20c3dc639c1292697a2255442f94c6", "title": "Tutoring Specialist - Freelance AI Trainer Project", "employer_name": "Agency", "employer_slug": "agency", "location_text": "World Wide - Remote", "country": "unknown", "employment_type": "contract", "remote_status": "remote", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": 0, "timezone_overlap_hours": 3, "salary_min": 6, "salary_max": 65, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "hour", "base_salary_min": 6, "base_salary_max": 65, "salary_disclosed": true, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "yc", "sequoia" ], "posted_at": "2026-06-07T17:58:24.000Z", "apply_url": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "apply_url_verified": false, "ats": "greenhouse", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Tutoring Specialist - Freelance AI Trainer Project World Wide - Remote Are you an experienced instructional professional with hands-on knowledge of pedagogy, complex concept breakdown, and clear communication eager to independently contract and help shape how AI understands educational work? As AI systems increasingly model instructional operations and teaching workflows, their accuracy depends on training data grounded in real learning environments. That training data begins with experts who know the work firsthand. We're seeking independent Instructional Experts with tangible, hands-on experience teaching, tutoring, or building curriculum. This includes experience with university instruction, bootcamp mentoring, corporate enablement, or online course creation. This project will include challenging AI models on realistic educational scenarios involving reasoning quality, instructional value, pedagogical logic, and the creation of \"gold standard\" teaching exemplars. Contractors will engage the model on complex instructional scenarios, validate whether its understanding of pedagogical concepts reflects best-in-class teaching practice, evaluate AI outputs for clarity and correctness, analyze subtle reasoning errors, document gaps in logic, and provide structured, rewritten explanations to elevate how the model reasons and teaches. Deep expertise in instruction and structured reasoning is required to complete these deliverables, including the ability to communicate with high empathy and high rigor. Prior experience as a TA, tutor, lecturer, or course creator is highly valued, particularly with platforms like Udemy, Coursera, or Udacity. Clear, native-level English communication and the ability to accurately explain and document complex concepts in clear, logically sequenced steps are essential. Ready to turn your instructional and pedagogical experience into the", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 55, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "remote_status": { "field": "remote_status", "source": "rule:remote_status", "db_column": "remote_status" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "days_in_office": { "field": "days_in_office", "source": "rule:remote_status", "db_column": "days_in_office" }, "contractor_type": { "field": "contractor_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "contractor_type" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "teaching_education", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": "Professional Services", "employer_industry_source": "source_sector", "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.1be95940a74174f048", "query_id": "gq_027d2641909897d49713", "job_id": "cc20c3dc639c1292697a2255442f94c6", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Tutoring Specialist - Freelance AI Trainer Project World Wide - Remote Are you an experienced instructional professional with hands-on knowledge of pedagogy, complex concept breakdown, and clear communication eager to independently contract and help shape how AI understands educational work? As AI systems increasingly model instructional operations and teaching workflows, their accuracy depends on training data grounded in real learning environments. That training data begins with experts who know the work firsthand. We're seeking independent Instructional Experts with tangible, hands-on experience teaching, tutoring, or building curriculum. This includes experience with university instruction, bootcamp mentoring, corporate enablement, or online course creation. This project will include challenging AI models on realistic educational scenarios involving reasoning quality, instructional value, pedagogical logic, and the creation of \"gold standard\" teaching exemplars. Contractors will engage the model on complex instructional scenarios, validate whether its understanding of pedagogical concepts reflects best-in-class teaching practice, evaluate AI outputs for clarity and correctness, analyze subtle reasoning errors, document gaps in logic, and provide structured, rewritten explanations to elevate how the model reasons and teaches. Deep expertise in instruction and structured reasoning is required to complete these deliverables, including the ability to communicate with high empathy and high rigor. Prior experience as a TA, tutor, lecturer, or course creator is highly valued, particularly with platforms like Udemy, Coursera, or Udacity. Clear, native-level English communication and the ability to accurately explain and document complex concepts in clear, logically sequenced steps are essential. Ready to turn your instructional and pedagogical experience into the", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:cc20c3dc639c1292697a2255442f94c6:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.37e2145356f0d19b4b", "query_id": "gq_027d2641909897d49713", "job_id": "cc20c3dc639c1292697a2255442f94c6", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Tutoring Specialist - Freelance AI Trainer Project", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:cc20c3dc639c1292697a2255442f94c6:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.82b56a0931df979500", "query_id": "gq_027d2641909897d49713", "job_id": "cc20c3dc639c1292697a2255442f94c6", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Tutoring Specialist - Freelance AI Trainer Project", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:47d20d9e7013a49138ec40eb", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.49705ec7e72f14bbfa", "query_id": "gq_027d2641909897d49713", "job_id": "cc20c3dc639c1292697a2255442f94c6", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Tutoring Specialist - Freelance AI Trainer Project", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "remote_status": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "source_values": [ "rule:remote_status" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://job-boards.eu.greenhouse.io/agency/jobs/4796064101", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "0af6bc4ba872b5d95f2fddf661e35008", "title": "Principal AI Engineer", "employer_name": "RELX", "employer_slug": "relx", "location_text": "United Kingdom", "country": "GB", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T00:00:00.000Z", "apply_url": "https://relx.wd3.myworkdayjobs.com/relx/job/United-Kingdom/Principal-AI-Engineer_R114326", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Principal AI Engineer United Kingdom posted: Posted 2 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "staff_plus", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 8, "years_experience_max": 12, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.006dc573983ccb44fc", "query_id": "gq_027d2641909897d49713", "job_id": "0af6bc4ba872b5d95f2fddf661e35008", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Principal AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:0716e28000408c55966914ee", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.e51c7bb6a486f910ff", "query_id": "gq_027d2641909897d49713", "job_id": "0af6bc4ba872b5d95f2fddf661e35008", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Principal AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.c8dc98a715b96697d3", "query_id": "gq_027d2641909897d49713", "job_id": "0af6bc4ba872b5d95f2fddf661e35008", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:0af6bc4ba872b5d95f2fddf661e35008:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/United-Kingdom/Principal-AI-Engineer_R114326", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/United-Kingdom/Principal-AI-Engineer_R114326", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "title": "AI Lab - Machine Learning Engineer", "employer_name": "Hewlett-Packard", "employer_slug": "hewlett-packard", "location_text": "Sant Cugat del Valles, Barcelona, Spain", "country": "ES", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://hp.eightfold.ai/careers/job/28359629", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Lab - Machine Learning Engineer Sant Cugat del Valles, Barcelona, Spain", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.b0bd053bed358aca0d", "query_id": "gq_027d2641909897d49713", "job_id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "AI Lab - Machine Learning Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:7fd0b600e17935111760eed5", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.e03990a99b10e6e191", "query_id": "gq_027d2641909897d49713", "job_id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "AI Lab - Machine Learning Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.38c989a7c21e6fc9cf", "query_id": "gq_027d2641909897d49713", "job_id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:44b5e12d2e439bd9fa3a3ab4c2e89a9d:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://hp.eightfold.ai/careers/job/28359629", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://hp.eightfold.ai/careers/job/28359629", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "1d67e0294b385e6616b5f3c119d14e0b", "title": "Product Marketing Manager, GTM – AI Agent Platform", "employer_name": "PatSnap", "employer_slug": "patsnap", "location_text": "Shanghai", "country": "CN", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-05-01T06:24:34.837Z", "apply_url": "https://jobs.lever.co/patsnap/b85aa927-6566-4d67-8d6c-b2c27776edf2", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Product Marketing Manager, GTM – AI Agent Platform Shanghai About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. What You'll Do - Develop clear value propositions, positioning, and messaging for our AI Agent Platform in global B2B SaaS markets. - Translate product features and AI capabilities into customer-facing narratives, use cases, talk tracks, and GTM materials. - Work with product, sales, and customer-facing teams to support product launches, market education, and customer conversations. - Track the competitive landscape and market trends to support differentiated positioning", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 2, "years_experience_max": 6, "role_function": "marketing", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.e81c01abf140927cc0", "query_id": "gq_027d2641909897d49713", "job_id": "1d67e0294b385e6616b5f3c119d14e0b", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Product Marketing Manager, GTM – AI Agent Platform Shanghai About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. What You'll Do - Develop clear value propositions, positioning, and messaging for our AI Agent Platform in global B2B SaaS markets. - Translate product features and AI capabilities into customer-facing narratives, use cases, talk tracks, and GTM materials. - Work with product, sales, and customer-facing teams to support product launches, market education, and customer conversations. - Track the competitive landscape and market trends to support differentiated positioning", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:1d67e0294b385e6616b5f3c119d14e0b:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.location_text.448e831425a926195a", "query_id": "gq_027d2641909897d49713", "job_id": "1d67e0294b385e6616b5f3c119d14e0b", "signal_type": "query_match", "display_text": "Location: \"ai\"", "tooltip": "Location matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "location_text", "source_value": "Shanghai", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:1d67e0294b385e6616b5f3c119d14e0b:location:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.d95725c0161525a70c", "query_id": "gq_027d2641909897d49713", "job_id": "1d67e0294b385e6616b5f3c119d14e0b", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Product Marketing Manager, GTM – AI Agent Platform", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:1d67e0294b385e6616b5f3c119d14e0b:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.525a9b144192e655a9", "query_id": "gq_027d2641909897d49713", "job_id": "1d67e0294b385e6616b5f3c119d14e0b", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Product Marketing Manager, GTM – AI Agent Platform", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:94479cdd5b1e84608d9179fb", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.799a3019303e1d2c78", "query_id": "gq_027d2641909897d49713", "job_id": "1d67e0294b385e6616b5f3c119d14e0b", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Product Marketing Manager, GTM – AI Agent Platform", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/patsnap/b85aa927-6566-4d67-8d6c-b2c27776edf2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/patsnap/b85aa927-6566-4d67-8d6c-b2c27776edf2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/patsnap/b85aa927-6566-4d67-8d6c-b2c27776edf2", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "486aeffb411954a09d0a7219c5b0e578", "title": "Senior Agentic AI Engineer", "employer_name": "Adobe Inc.", "employer_slug": "adobe", "location_text": "Yerevan", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-12T00:00:00.000Z", "apply_url": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Yerevan/Senior-Agentic-AI-Engineer_R165482", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Agentic AI Engineer Yerevan posted: Posted 30+ Days Ago", "parental_leave_weeks": 16, "non_birth_parent_leave_weeks": 16, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 90, "benefit_verified": true, "benefit_last_verified": "2026-05-07", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "parental_leave_weeks": { "field": "parental_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "parental_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" }, "non_birth_parent_leave_weeks": { "field": "non_birth_parent_leave_weeks", "source": "https://benefits.adobe.com/us/time-off/leaves-of-absence", "db_column": "non_birth_parent_leave_weeks", "source_url": "https://benefits.adobe.com/us/time-off/leaves-of-absence" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 5, "years_experience_max": 9, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": "Technology", "employer_industry_source": "source_sector", "employer_size": "5000+", "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.d1c0a6ceafb65b522e", "query_id": "gq_027d2641909897d49713", "job_id": "486aeffb411954a09d0a7219c5b0e578", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Senior Agentic AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:c991a6d434ca1b444bfdca7f", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.ec2d3b82632d5b73d8", "query_id": "gq_027d2641909897d49713", "job_id": "486aeffb411954a09d0a7219c5b0e578", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Senior Agentic AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.5cd6f317af7ff7b1fb", "query_id": "gq_027d2641909897d49713", "job_id": "486aeffb411954a09d0a7219c5b0e578", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:486aeffb411954a09d0a7219c5b0e578:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": "Employer benefits source", "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/796343/000079634326000003/adbe-20251128.htm" ], "checked_at": null }, "parental_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Yerevan/Senior-Agentic-AI-Engineer_R165482", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "non_birth_parent_leave_weeks": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Yerevan/Senior-Agentic-AI-Engineer_R165482", "source_values": [ "https://benefits.adobe.com/us/time-off/leaves-of-absence" ], "checked_at": "2026-05-07" }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-05-07" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Yerevan/Senior-Agentic-AI-Engineer_R165482", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://adobe.wd5.myworkdayjobs.com/external_experienced/job/Yerevan/Senior-Agentic-AI-Engineer_R165482", "source_values": [ "rule" ], "checked_at": null }, "employer_industry": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": null, "source_values": [ "source_sector" ], "checked_at": null } } }, { "id": "b5013116c00d4d5eb15252db06906c87", "title": "Product Marketing Manager, GTM – AI Agent Platform（Intellectual Property）", "employer_name": "PatSnap", "employer_slug": "patsnap", "location_text": "Singapore", "country": "SG", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-05-01T06:20:37.782Z", "apply_url": "https://jobs.lever.co/patsnap/af75d79b-7bb5-4610-bcd4-dc082313b473", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Product Marketing Manager, GTM – AI Agent Platform（Intellectual Property） Singapore About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. What You'll Do - Develop clear value propositions, positioning, and messaging for our AI Agent Platform in global B2B SaaS markets. - Translate product features and AI capabilities into customer-facing narratives, use cases, talk tracks, and GTM materials. - Work with product, sales, and customer-facing teams to support product launches, market education, and customer conversations. - Track the competitive landscape and market trends to support differentiated", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 43, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "company_stage": { "field": "company_stage", "source": "llm:greenfield:inv_371_postfix", "db_column": "company_stage" }, "customer_type": { "field": "customer_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "customer_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 2, "years_experience_max": 6, "role_function": "marketing", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": "growth-stage", "company_stage_source": "llm:greenfield:inv_371_postfix", "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 45, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.d37f76fb543fa3f2a1", "query_id": "gq_027d2641909897d49713", "job_id": "b5013116c00d4d5eb15252db06906c87", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Product Marketing Manager, GTM – AI Agent Platform（Intellectual Property） Singapore About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. About the Role We are looking for a Product Marketing Manager, GTM to help bring our AI Agent Platform to global markets, with a primary focus on North America and Europe. This role sits at the intersection of product, market, customer insight, and go-to-market execution. You will translate product capabilities into clear value propositions, build messaging and positioning for global audiences, and support launch and adoption across different market segments. The ideal candidate is AI-fluent, commercially minded, and comfortable working in English as a professional working language. What You'll Do - Develop clear value propositions, positioning, and messaging for our AI Agent Platform in global B2B SaaS markets. - Translate product features and AI capabilities into customer-facing narratives, use cases, talk tracks, and GTM materials. - Work with product, sales, and customer-facing teams to support product launches, market education, and customer conversations. - Track the competitive landscape and market trends to support differentiated", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:b5013116c00d4d5eb15252db06906c87:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.ce395528aa49238d16", "query_id": "gq_027d2641909897d49713", "job_id": "b5013116c00d4d5eb15252db06906c87", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Product Marketing Manager, GTM – AI Agent Platform（Intellectual Property）", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:b5013116c00d4d5eb15252db06906c87:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.fe3c4f037acd8e4d23", "query_id": "gq_027d2641909897d49713", "job_id": "b5013116c00d4d5eb15252db06906c87", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Product Marketing Manager, GTM – AI Agent Platform（Intellectual Property）", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:222530524aaaeb54abd6d124", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.5bdcd5c811c01691de", "query_id": "gq_027d2641909897d49713", "job_id": "b5013116c00d4d5eb15252db06906c87", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Product Marketing Manager, GTM – AI Agent Platform（Intellectual Property）", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/patsnap/af75d79b-7bb5-4610-bcd4-dc082313b473", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/patsnap/af75d79b-7bb5-4610-bcd4-dc082313b473", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "company_stage": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/patsnap/af75d79b-7bb5-4610-bcd4-dc082313b473", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "80562e0f20a686328c2e4f2b35e2a9b6", "title": "AI Lab - Junior Machine Learning Engineer", "employer_name": "Hewlett-Packard", "employer_slug": "hewlett-packard", "location_text": "Sant Cugat del Valles, Barcelona, Spain", "country": "ES", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options", "espp", "profit_share" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-12T10:25:24.000Z", "apply_url": "https://hp.eightfold.ai/careers/job/28359544", "apply_url_verified": false, "ats": "eightfold", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Lab - Junior Machine Learning Engineer Sant Cugat del Valles, Barcelona, Spain", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "entry", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 0, "years_experience_max": 4, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.e09ecf54785b09b6ad", "query_id": "gq_027d2641909897d49713", "job_id": "80562e0f20a686328c2e4f2b35e2a9b6", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "AI Lab - Junior Machine Learning Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:8c678f7ed92a3c47363b0a77", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.52f207e0efe51af708", "query_id": "gq_027d2641909897d49713", "job_id": "80562e0f20a686328c2e4f2b35e2a9b6", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "AI Lab - Junior Machine Learning Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.8781442b427948345b", "query_id": "gq_027d2641909897d49713", "job_id": "80562e0f20a686328c2e4f2b35e2a9b6", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:80562e0f20a686328c2e4f2b35e2a9b6:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/47217/000004721725000071/hpq-20251031.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://hp.eightfold.ai/careers/job/28359544", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://hp.eightfold.ai/careers/job/28359544", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "2d915f45443f4f68f31b36aa283c84a2", "title": "Senior Machine Learning Engineer , AI Platform", "employer_name": "Whoop", "employer_slug": "whoop", "location_text": "Boston, MA", "country": "US", "employment_type": "full_time", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 6, "salary_min": 150000, "salary_max": 210000, "salary_min_source": null, "salary_max_source": null, "salary_currency": "USD", "salary_type": "base", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": "year", "base_salary_min": 150000, "base_salary_max": 210000, "salary_disclosed": true, "equity_included": true, "equity_included_source": null, "equity_type": [ "options" ], "k401_match": null, "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [], "k401_contribution_source_url": null, "k401_contribution_source_fields": [], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2025-12-04T15:18:17.732Z", "apply_url": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "apply_url_verified": false, "ats": "lever", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Senior Machine Learning Engineer , AI Platform Boston, MA At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day. WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP's AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components of the AI Platform that power our internal AI Studio: evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. You will partner closely with product and data science to translate real member needs into reliable, impactful AI systems that improve continuously based on real-world usage. At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day. WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP's AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 47, "benefit_verified": false, "benefit_last_verified": null, "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": "2026-06-20T05:42:05.724Z", "llm_extraction_run_id": "postfix_final_004037", "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "years_min": { "field": "years_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "years_experience_min" }, "salary_max": { "field": "salary_max", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_max" }, "salary_min": { "field": "salary_min", "source": "llm:greenfield:inv_371_postfix", "db_column": "base_salary_min" }, "tech_stack": { "field": "tech_stack", "source": "llm:greenfield:inv_371_postfix", "db_column": "tech_stack" }, "role_family": { "field": "role_family", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_family" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "llm:greenfield:inv_371_postfix", "db_column": "role_function" }, "salary_period": { "field": "salary_period", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_period" }, "equity_offered": { "field": "equity_offered", "source": "llm:greenfield:inv_371_postfix", "db_column": "equity_offered" }, "contractor_type": { "field": "contractor_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "contractor_type" }, "employment_type": { "field": "employment_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "employment_type" }, "equity_included": { "field": "equity_included", "source": "derived:greenfield:inv_371_postfix", "db_column": "equity_included" }, "salary_currency": { "field": "salary_currency", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_currency" }, "salary_disclosed": { "field": "salary_disclosed", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_disclosed" }, "visa_sponsorship": { "field": "visa_sponsorship", "source": "llm:greenfield:inv_371_postfix", "db_column": "visa_sponsorship" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" }, "visible_salary_max": { "field": "visible_salary_max", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_max" }, "visible_salary_min": { "field": "visible_salary_min", "source": "derived:greenfield:inv_371_postfix", "db_column": "salary_min" } }, "seniority": "senior", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "engineering", "role_function_source": "llm:greenfield:inv_371_postfix", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": "51-200", "quality_score": 55, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": true, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.aa13ad248c39fd3a47", "query_id": "gq_027d2641909897d49713", "job_id": "2d915f45443f4f68f31b36aa283c84a2", "signal_type": "query_match", "display_text": "Description: \"ai\"", "tooltip": "Description matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "description_excerpt", "source_value": "Senior Machine Learning Engineer , AI Platform Boston, MA At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day. WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP's AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components of the AI Platform that power our internal AI Studio: evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. You will partner closely with product and data science to translate real member needs into reliable, impactful AI systems that improve continuously based on real-world usage. At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day. WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP's AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:2d915f45443f4f68f31b36aa283c84a2:description:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.8bdde7fd64c7d6a294", "query_id": "gq_027d2641909897d49713", "job_id": "2d915f45443f4f68f31b36aa283c84a2", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title matched \"ai\" from your search.", "source_binding": "bm25_field_evidence", "source_field": "title", "source_value": "Senior Machine Learning Engineer , AI Platform", "matched_input": "ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:2d915f45443f4f68f31b36aa283c84a2:title:ai", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.2420e4c600e308aea8", "query_id": "gq_027d2641909897d49713", "job_id": "2d915f45443f4f68f31b36aa283c84a2", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "Senior Machine Learning Engineer , AI Platform", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:403d167e608f5939fd34e52f", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.1cda028d1189803fce", "query_id": "gq_027d2641909897d49713", "job_id": "2d915f45443f4f68f31b36aa283c84a2", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "Senior Machine Learning Engineer , AI Platform", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } } ], "parental_leave_source_label": null, "k401_match_source_label": null, "k401_contribution_source_label": null, "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "salary_min": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_max": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "salary_type": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "equity_included": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "source_values": [ "derived:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://jobs.lever.co/whoop/69b264af-4223-48d3-964d-5f5ba883a95d", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": "2026-06-20T05:42:05.724Z" } } }, { "id": "459318b567253f17361875f5c238beb6", "title": "AI Engineer", "employer_name": "Kyndryl", "employer_slug": "kyndryl", "location_text": "CRAFZ Heredia (CRAFZ) Afz", "country": "unknown", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": true, "equity_included_source": null, "equity_type": [ "rsu", "options" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-05-28T00:00:00.000Z", "apply_url": "https://kyndryl.wd5.myworkdayjobs.com/KyndrylProfessionalCareers/job/CRAFZ-Heredia-CRAFZ-Afz/AI-Engineer_R-61862", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer CRAFZ Heredia (CRAFZ) Afz posted: Posted 15 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "equity_type": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "equity_included": { "source": "sec_10k", "source_url": "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm", "source_fields": [ "equity_offered", "equity_type" ] }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.677c339f9ddb073d89", "query_id": "gq_027d2641909897d49713", "job_id": "459318b567253f17361875f5c238beb6", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:71c150f42dc6b9b8e55e7f11", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.8cf9d73c71111022b7", "query_id": "gq_027d2641909897d49713", "job_id": "459318b567253f17361875f5c238beb6", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.dbb1355965884fd78e", "query_id": "gq_027d2641909897d49713", "job_id": "459318b567253f17361875f5c238beb6", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:459318b567253f17361875f5c238beb6:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "government", "verified": true, "label": "Verified - SEC 10-K", "source_label": "SEC 10-K", "href": "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm", "source_values": [ "sec_10k", "https://www.sec.gov/Archives/edgar/data/1867072/000110465926067881/kd-20260331x10k.htm" ], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://kyndryl.wd5.myworkdayjobs.com/KyndrylProfessionalCareers/job/CRAFZ-Heredia-CRAFZ-Afz/AI-Engineer_R-61862", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://kyndryl.wd5.myworkdayjobs.com/KyndrylProfessionalCareers/job/CRAFZ-Heredia-CRAFZ-Afz/AI-Engineer_R-61862", "source_values": [ "rule" ], "checked_at": null } } }, { "id": "718f494233a68db38002fb95ba1af728", "title": "AI Engineer", "employer_name": "RELX", "employer_slug": "relx", "location_text": "London", "country": "GB", "employment_type": "unknown", "remote_status": "unspecified", "remote_status_source": null, "remote_status_enriched_at": null, "days_in_office": null, "timezone_overlap_hours": 3, "salary_min": null, "salary_max": null, "salary_min_source": null, "salary_max_source": null, "salary_currency": "UNSPECIFIED", "salary_type": "unknown", "salary_type_source": null, "salary_type_enriched_at": null, "salary_period": null, "base_salary_min": null, "base_salary_max": null, "salary_disclosed": false, "equity_included": false, "equity_included_source": null, "equity_type": [ "none" ], "k401_match": "yes", "match_401k_pct": null, "match_401k_pct_source": null, "k401_match_source_url": null, "k401_match_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "k401_contribution_source_url": null, "k401_contribution_source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "profit_sharing": false, "bonus_offered": false, "mental_health_support": null, "childcare_subsidy": null, "fertility_family_building_benefits": null, "adoption_assistance_offered": null, "surrogacy_assistance_offered": null, "student_loan_repayment_offered": null, "learning_budget_offered": null, "relocation_assistance": null, "top_startup_sources": [], "posted_at": "2026-06-10T00:00:00.000Z", "apply_url": "https://relx.wd3.myworkdayjobs.com/relx/job/London/AI-Engineer_R114346-1", "apply_url_verified": false, "ats": "workday", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "AI Engineer London posted: Posted 2 Days Ago", "parental_leave_weeks": null, "non_birth_parent_leave_weeks": null, "parental_leave_weeks_source": null, "non_birth_parent_leave_weeks_source": null, "parental_leave_source_url": null, "pto_days": null, "unlimited_pto": false, "sabbatical_eligible": false, "family_friendly_score": 40, "benefit_verified": true, "benefit_last_verified": "2026-06-07T00:00:00Z", "hire_states_allowed": [], "state_eligibility_source": null, "state_eligibility_enriched_at": null, "llm_quality_pass_at": null, "llm_signals_at": null, "llm_extraction_run_id": null, "llm_extraction_extracted_at": null, "llm_extraction_field_sources": { "seniority": { "field": "seniority", "source": "llm:greenfield:inv_371_postfix", "db_column": "seniority" }, "k401_match": { "source": "dol_form_5500", "source_url": null, "source_fields": [ "EMPLR_CONTRIB_INCOME_AMT" ], "source_label": "DOL Form 5500 filing" }, "salary_type": { "field": "salary_type", "source": "llm:greenfield:inv_371_postfix", "db_column": "salary_type" }, "role_function": { "field": "role_function", "source": "rule", "db_column": "role_function" }, "education_required": { "field": "education_required", "source": "llm:greenfield:inv_371_postfix", "db_column": "education_required" } }, "seniority": "mid", "seniority_source": "llm:greenfield:inv_371_postfix", "years_experience_min": 3, "years_experience_max": 7, "role_function": "data", "role_function_source": "rule", "company_stage": null, "company_stage_source": null, "employer_industry": null, "employer_industry_source": null, "employer_size": null, "quality_score": 35, "travel_pct": null, "requires_shift": null, "shift_type": "unknown", "shift_type_source": null, "weekend_work": "unknown", "weekend_work_source": null, "relocation_assistance_source": null, "contractor_w2": "unknown", "required_timezone": null, "fertility_family_building_benefits_source": null, "mental_health_support_source": null, "adoption_assistance_offered_source": null, "childcare_subsidy_source": null, "learning_budget_offered_source": null, "surrogacy_assistance_offered_source": null, "cover_letter_required": null, "cover_letter_required_source": null, "assessment_required": null, "assessment_required_source": null, "application_deadline": null, "application_deadline_source": null, "visa_sponsorship": false, "us_citizenship_required": false, "security_clearance": "none", "education_required": "none", "roll_up_count": null, "roll_up_total_locations": null, "explanations": [ { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.title.53a79cb412b2d6aabd", "query_id": "gq_027d2641909897d49713", "job_id": "718f494233a68db38002fb95ba1af728", "signal_type": "query_match", "display_text": "Title: semantic match", "tooltip": "Title provided semantic evidence for your search intent.", "source_binding": "reranker_semantic_evidence", "source_field": "title", "source_value": "AI Engineer", "matched_input": "clearly ai", "derivation_source": "rerank_result.semantic_evidence", "candidate_evidence_id": null, "rerank_evidence_id": "rerank:f5b11fd81a262d5d6240dade", "taxonomy_alias_id": null, "oracle_verification_method": "reranker_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 86, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.title.ea9a88ea88f3dad550", "query_id": "gq_027d2641909897d49713", "job_id": "718f494233a68db38002fb95ba1af728", "signal_type": "query_match", "display_text": "Title: \"ai\"", "tooltip": "Title contains \"ai\" from your search.", "source_binding": "token_match", "source_field": "title", "source_value": "AI Engineer", "matched_input": "ai", "derivation_source": "row_field", "candidate_evidence_id": null, "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "row_field_contains", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 80, "mobile_priority": 2, "ui": { "icon": "SearchCheck", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.semantic.role_function.20dd8f82b0bdd66ba6", "query_id": "gq_027d2641909897d49713", "job_id": "718f494233a68db38002fb95ba1af728", "signal_type": "query_match", "display_text": "Role: semantic match", "tooltip": "Role provided semantic evidence for your search intent.", "source_binding": "vector_semantic_evidence", "source_field": "role_function", "source_value": "data", "matched_input": "clearly ai", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_027d2641909897d49713:718f494233a68db38002fb95ba1af728:vector", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": false, "priority": 74, "mobile_priority": 2, "ui": { "icon": "Sparkles", "tone": "match", "href": null } } ], "source_label": "DOL Form 5500 filing", "parental_leave_source_label": null, "k401_match_source_label": "DOL Form 5500 filing", "k401_contribution_source_label": "DOL Form 5500 filing", "apply_url_checked_at": null, "apply_url_verification_status": "not_reachable_or_not_checked", "apply_url_verification_label": "Not checked or not reachable at last crawl", "field_source_signals": { "equity_included": { "tier": "inferred", "verified": false, "label": "Inferred - source not recorded", "source_label": "source not recorded", "href": null, "source_values": [], "checked_at": null }, "k401_match": { "tier": "government", "verified": true, "label": "Verified - DOL Form 5500", "source_label": "DOL Form 5500", "href": null, "source_values": [ "dol_form_5500", "EMPLR_CONTRIB_INCOME_AMT" ], "checked_at": "2026-06-07T00:00:00Z" }, "seniority": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/London/AI-Engineer_R114346-1", "source_values": [ "llm:greenfield:inv_371_postfix" ], "checked_at": null }, "role_function": { "tier": "posting", "verified": true, "label": "From the posting", "source_label": "the posting", "href": "https://relx.wd3.myworkdayjobs.com/relx/job/London/AI-Engineer_R114346-1", "source_values": [ "rule" ], "checked_at": null } } } ], "total": 3596, "page": 1, "per_page": 24, "applied_filters": { "q": "Clearly AI" }, "hidden_unknown_benefits_count": 0, "hidden_quality_floor_count": 0, "quality_floor": "default", "search_profile": { "profile_id": "inv382.d6.pg_textsearch_bge_small_rrf.v1", "bm25_extension": "pg_textsearch", "vector_model": "BAAI/bge-small-en-v1.5", "vector_model_version": "v1.5", "fusion_method": "rrf" }, "explanation_context": { "non_trivial_query": true, "query_terms": [ "clearly", "ai" ], "active_filter_keys": [], "visible_signal_limit": 3, "visible_trust_limit": 2 }, "event_context": { "query_context": { "query_id": "ad7df84b-9f88-4dbc-859a-1cb58aa602f1", "issued_at": "2026-11-13T11:23:06.633Z", "route": "/jobs", "page": 1, "per_page": 24, "total_results": 3596, "sort": "relevance", "ranking_policy": "hybrid_rrf_rerank", "ranking_policy_version": "inv382.jobs.search.v2", "query_hash": "hmac_sha256:Lb_Jvy3GUGgKteV-1VZaNTaamrKjRBmyqISBvwwks0Q", "filter_hash": "hmac_sha256:6CBErDPXOFVCSNkSGbTmuw6GxoMjwSLro0KqZMtxL_0", "query_features": { "has_q": true, "q_term_count": 2, "q_length_bucket": "1_15", "q_pii_redacted": false, "state_count": 0, "benefit_filters": [], "quality_floor": "default" }, "exposures": [ { "result_id": "2d9cadf9c4a2f7c464b68b7b9c2bf5a0", "position": 1, "page_position": 1, "retrieval_features": { "bm25_score": -8.761658906936646, "vector_score": 0, "rrf_score": 0.014705882352941176, "rerank_score": 8.657271385192871, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "4f1c1848ab82052577e9d4ae4e4de869", "position": 2, "page_position": 2, "retrieval_features": { "bm25_score": -8.761658906936646, "vector_score": 0, "rrf_score": 0.014492753623188406, "rerank_score": 8.490092277526855, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "562947d0029ba29614cc23b7b5ad7239", "position": 3, "page_position": 3, "retrieval_features": { "bm25_score": -10.106952667236328, "vector_score": 0.2887963652610779, "rrf_score": 0.03252247488101534, "rerank_score": 8.371845245361328, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "7dac22dc8b07ff02d30bd36f171a5105", "position": 4, "page_position": 4, "retrieval_features": { "bm25_score": -8.517690420150757, "vector_score": 0, "rrf_score": 0.013888888888888888, "rerank_score": 7.96375846862793, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "addb6ece698d4434b71154d8a0bbb04b", "position": 5, "page_position": 5, "retrieval_features": { "bm25_score": -8.761658906936646, "vector_score": 0, "rrf_score": 0.014285714285714285, "rerank_score": 7.891701698303223, "text_match_title": false, "text_match_employer": true, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "e48e0a3b26b9943e4e10f3a9e4dfcd87", "position": 6, "page_position": 6, "retrieval_features": { "bm25_score": -10.06907033920288, "vector_score": 0.2991479426368455, "rrf_score": 0.028474711270410194, "rerank_score": 7.756418228149414, "text_match_title": false, "text_match_employer": true, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 45 } }, { "result_id": "962fe4f9730385011447431106d66715", "position": 7, "page_position": 7, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2922804355621338, "rrf_score": 0.015873015873015872, "rerank_score": 0.9632436633110046, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 154, "quality_score": 35 } }, { "result_id": "935b0898508dc89e2f72e49009f4a66f", "position": 8, "page_position": 8, "retrieval_features": { "bm25_score": -9.030349254608154, "vector_score": 0, "rrf_score": 0.015384615384615385, "rerank_score": 0.29277724027633667, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 191, "quality_score": 55 } }, { "result_id": "be5956e6d7ff7bb5d9d101bb86947b05", "position": 9, "page_position": 9, "retrieval_features": { "bm25_score": -9.513006687164307, "vector_score": 0, "rrf_score": 0.015625, "rerank_score": -0.5470076203346252, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 191, "quality_score": 55 } }, { "result_id": "6bd762860b96b1fc324e69514510ac7b", "position": 10, "page_position": 10, "retrieval_features": { "bm25_score": 0, "vector_score": 0.29811131954193115, "rrf_score": 0.0136986301369863, "rerank_score": -1.3157860040664673, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 155, "quality_score": 35 } }, { "result_id": "e3cf7f0fd074ec5454d1178d48fed01f", "position": 11, "page_position": 11, "retrieval_features": { "bm25_score": 0, "vector_score": 0.29659060856159747, "rrf_score": 0.013888888888888888, "rerank_score": -2.20341420173645, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 155, "quality_score": 35 } }, { "result_id": "a33f6668845b5d0d8559c2144d10a952", "position": 12, "page_position": 12, "retrieval_features": { "bm25_score": -9.897270202636719, "vector_score": 0, "rrf_score": 0.015873015873015872, "rerank_score": -2.752074718475342, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 158, "quality_score": 55 } }, { "result_id": "ce4a501fe3bac4a30b83f340bd9ce416", "position": 13, "page_position": 13, "retrieval_features": { "bm25_score": 0, "vector_score": 0.29825226674960326, "rrf_score": 0.013513513513513514, "rerank_score": -3.3141939640045166, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 35 } }, { "result_id": "e8650617aebb43bd6d8bf170a6d1088e", "position": 14, "page_position": 14, "retrieval_features": { "bm25_score": -8.429685115814209, "vector_score": 0, "rrf_score": 0.013513513513513514, "rerank_score": -4.203922271728516, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": true, "salary_disclosed": true, "posted_age_days": 168, "quality_score": 55 } }, { "result_id": "cc20c3dc639c1292697a2255442f94c6", "position": 15, "page_position": 15, "retrieval_features": { "bm25_score": -8.50559949874878, "vector_score": 0, "rrf_score": 0.0136986301369863, "rerank_score": -4.336755275726318, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 158, "quality_score": 55 } }, { "result_id": "0af6bc4ba872b5d95f2fddf661e35008", "position": 16, "page_position": 16, "retrieval_features": { "bm25_score": 0, "vector_score": 0.29619598388671875, "rrf_score": 0.014285714285714285, "rerank_score": -4.473478317260742, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 35 } }, { "result_id": "44b5e12d2e439bd9fa3a3ab4c2e89a9d", "position": 17, "page_position": 17, "retrieval_features": { "bm25_score": 0, "vector_score": 0.29859189399529007, "rrf_score": 0.013333333333333334, "rerank_score": -4.5834784507751465, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 154, "quality_score": 35 } }, { "result_id": "1d67e0294b385e6616b5f3c119d14e0b", "position": 18, "page_position": 18, "retrieval_features": { "bm25_score": -8.941426277160645, "vector_score": 0, "rrf_score": 0.015151515151515152, "rerank_score": -4.814993381500244, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 196, "quality_score": 45 } }, { "result_id": "486aeffb411954a09d0a7219c5b0e578", "position": 19, "page_position": 19, "retrieval_features": { "bm25_score": 0, "vector_score": 0.28660154342651367, "rrf_score": 0.01639344262295082, "rerank_score": -4.936546325683594, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 185, "quality_score": 35 } }, { "result_id": "b5013116c00d4d5eb15252db06906c87", "position": 20, "page_position": 20, "retrieval_features": { "bm25_score": -8.941426277160645, "vector_score": 0, "rrf_score": 0.014925373134328358, "rerank_score": -4.951035022735596, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": false, "posted_age_days": 196, "quality_score": 45 } }, { "result_id": "80562e0f20a686328c2e4f2b35e2a9b6", "position": 21, "page_position": 21, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2927987575531006, "rrf_score": 0.015625, "rerank_score": -4.996680736541748, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 154, "quality_score": 35 } }, { "result_id": "2d915f45443f4f68f31b36aa283c84a2", "position": 22, "page_position": 22, "retrieval_features": { "bm25_score": -8.529037952423096, "vector_score": 0, "rrf_score": 0.014084507042253521, "rerank_score": -5.0337300300598145, "text_match_title": true, "text_match_employer": false, "role_match": false, "benefit_verified": false, "salary_disclosed": true, "posted_age_days": 343, "quality_score": 55 } }, { "result_id": "459318b567253f17361875f5c238beb6", "position": 23, "page_position": 23, "retrieval_features": { "bm25_score": 0, "vector_score": 0.29552499678581845, "rrf_score": 0.014705882352941176, "rerank_score": -5.054851055145264, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 169, "quality_score": 35 } }, { "result_id": "718f494233a68db38002fb95ba1af728", "position": 24, "page_position": 24, "retrieval_features": { "bm25_score": 0, "vector_score": 0.2928212285041809, "rrf_score": 0.015384615384615385, "rerank_score": -5.093514919281006, "text_match_title": true, "text_match_employer": false, "role_match": true, "benefit_verified": true, "salary_disclosed": false, "posted_age_days": 156, "quality_score": 35 } } ] }, "context_signature": "kj_HEM-3HFxBkBWwG-7non4zUsPqG__FIl8ysbRE8tY", "event_token": "kj_HEM-3HFxBkBWwG-7non4zUsPqG__FIl8ysbRE8tY" } }