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Sr. AI FDE

MEGAZONE - Rochester, NY, Rochester, New York, United States

Posted Jun 9, 2026

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

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

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.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Senior From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Company

Company stage
Growth-stage From the posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Sr. AI FDE Rochester, NY, Rochester, New York, United States Job Description At MegazoneCloud, we help the world's most innovative companies adopt AI that actually delivers - not pilots that stall, but production systems that get used. As an AI Forward Deployed Engineer (FDE) , you embed directly with global clients to drive the adoption of leading AI platforms and agentic developer tooling: generative and agentic AI solutions on AWS and Google Cloud, and agentic coding tools from Anthropic (Claude Code), OpenAI (Codex), and AWS (Kiro). You sit at the intersection of engineering and customer success - rapidly prototyping, integrating with client environments, and owning solutions from proof-of-concept through production and into real, measured adoption. This is an ownership role: you are accountable for outcomes that stick, not just deliverables that ship. You'll apply best-practice automation - infrastructure as code (IaC), CI/CD, and DevSecOps - to deliver AI workloads that meet demanding performance, security, and cost-efficiency targets. Key Responsibilities • Embed with customer teams to translate business problems into production AI architectures spanning models, data, application, and operations - owning the outcome end to end. • Design, build, and deploy LLM-powered applications - including RAG pipelines, agentic workflows, and orchestration frameworks - integrated with client data stores, APIs, and security controls. • Stand up the AWS and Google Cloud environments needed for AI services - enabling and configuring Amazon Bedrock, SageMaker, Google Vertex AI, and related resources (IAM roles, networking, model access, and service quotas) self-sufficiently within client guardrails, partnering

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