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You will build and maintain agent-run test harnesses, LLM graders, and evaluation logic for AI-based systems. Additionally, you will own release pipelines and improve the reliability of staging and demo environments.
This is a hands-on software engineering role focused on building the verification and release systems for an AI/ML product. You will develop agent-powered testing, reliable CI signals, and deployment workflows that help the team ship safer, more predictable releases.
Build and maintain agent-run test harnesses, LLM graders, and evaluation logic for AI-based systems.
Expand regression coverage and create automated release gates that identify unsafe changes with clear evidence.
Improve GitHub Actions workflows, container builds, CI health, and artifact publication.
Own release pipelines and improve the reliability of staging and demo environments.
Investigate quality gaps and incidents, then strengthen the systems that prevent them.
Seven to fifteen years of experience in quality, release, or platform engineering.
Recent hands-on experience applying AI-native methods to test or evaluate LLM or agentic systems, including LLM APIs, tool calling or MCP, and evaluations.
Strong experience with GitHub Actions and GitHub-based CI/CD, including container builds and pipeline automation.
Working knowledge of Python, TypeScript, Docker, Kubernetes, Helm, and at least one major cloud or data platform such as AWS, Azure, Databricks, or Snowflake.
Experience taking independent ownership of systems, ideally in a fast-moving startup or while modernizing established QA or DevOps practices.
Authorization to work in the US or Canada without visa sponsorship.
Base salary is $170,000 to $200,000 USD annually. Visa sponsorship is not available.
Remote, with New York, New York as the primary location.
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