Lead Software Engineer, Agentic AI Systems

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

Median wage (BLS OEWS)

$116,543 national median

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

41% above the BLS national median for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

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About this role

Lead Software Engineer, Agentic AI Systems Lehi, UT | Plano, TX At Collective Health, we're transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design. The Claims AI Automation team is currently evolving from traditional rule-based adjudication to an intelligence-driven platform. We are seeking a Lead Software Engineer who excels at high-level technical execution. This role is focused on the development and delivery of our Agentic AI strategy, turning architectural blueprints into production-ready systems. The ideal candidate will be the primary engine for building Python-based AI agents using the Google Cloud (GCP) ecosystem to automate complex claims workflows. You will be responsible for implementing sophisticated LLM behaviors using Gemini. What you will do: - Execute Agentic Workflows: Build and deploy sophisticated AI agents using Google Vertex AI and the Google Agent SDK (ADK) based on provided architectural specifications. - Develop and optimize agent behaviors using Gemini (Pro/Flash) with a focus on reliable tool-calling and multi-step reasoning; implement RAG and grounding strategies to ensure AI agents provide factual, data-driven responses derived from internal claims databases and policy documents. - Design and implement complex system instructions, few-shot prompting, and Chain-of-Thought reasoning to ensure agents handle claims logic with high precision, performing Supervised Fine-Tuning on Gemini models to improve domain-specific performance in adjudication and medical coding - Data & Messaging: Expert in SQL/PostgreSQ/AlloyDB/BigQueryUnderstand architectural decisions and actively drive reusable patterns for cloud-native, AI-enabled backend systems. - Design and implement Stateful

Read the full description at jobs.collectivehealth.com. FewerJobs shows a source-linked preview and links to the original posting.