Founding AI Quality & Release Engineer

This is the first dedicated quality-infrastructure hire at a well-backed AI/data startup, and it is a software engineering role through and through. You will own the full verification and release system, from agentic test harnesses and LLM graders to CI pipelines and deployment gates, making every green build trustworthy and every release uneventful. What You’ll Do

• Design, build, and maintain agentic test harnesses and LLM-based evaluation systems that run and grade tests automatically.
• Own regression coverage and release gates, ensuring unsafe builds are stopped with evidence rather than intuition.
• Develop and improve CI pipelines, artifact publication workflows, and container build automation using GitHub Actions.
• Maintain reliable demo and staging environments that faithfully represent production.
• Drive down bug-escape rates by closing gaps in the automated signal, not by adding manual test runs.
• Participate in business-hours incident escalations and make incidents rarer and easier to diagnose over time., Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machin…
• 10 hours ago, AI Engineer 4 (AI Foundations) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in…
• 10 hours ago, Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry lead…
• 1 day ago +

• 7 to 10 or more years of overall software or quality engineering experience.
• At least 1 year of hands-on experience building, testing, or evaluating agentic AI systems and LLM-based applications, applied within the last year.
• Deep proficiency with GitHub Actions and GitHub-based CI/CD, including container builds and pipeline automation.
• Strong command of Python and TypeScript; comfort with Docker, Kubernetes, and Helm.
• Familiarity with at least one major cloud or data platform such as AWS, Snowflake, Databricks, or Azure.
• Background in early-stage startups or in modernizing legacy QA and DevOps practices inside larger organizations.
• Demonstrated ability to take full ownership of systems and processes, make independent decisions, and execute without close guidance.
• Fully authorized to work in the US or Canada without visa sponsorship now or in the future.