
Founding AI Quality & Release Engineer
Required skills
- Python
- Software Engineering
- CI/CD
- GitHub Actions
- AI Verification
- LLM graders
- agent-run test harnesses
- Release Engineering
- artifact publication
- deployment pipelines
Nice to have
- TypeScript
- Snowflake Native Apps
- Playwright
- LLM-as-judge
- nondeterministic system testing
- startup quality infrastructure
Role summary
A seed-stage enterprise AI company is seeking a Founding AI Quality & Release Engineer. This is a software engineering role focused on building and owning the verification and release system for AI-driven data agents. Responsibilities include AI-powered verification (70%) using LLM graders and agent-run test harnesses, and release/environment engineering (30%) across CI, artifact publication, and deployment pipelines. The ideal candidate has 7-15 years of experience in quality, release, or platform engineering, with strong Python and software engineering fundamentals, CI/CD expertise (GitHub Actions), and experience with containerization and cloud deployment (Docker, Kubernetes, AWS).
Our client is a seed-stage enterprise AI company building autonomous data agents that execute complex engineering workflows inside customer-controlled cloud environments. Founded by early employees of a leading cloud data platform, the approximately 20-person team helps data organizations compress work that once took months into hours.
This is the company's first dedicated quality-infrastructure hire. It is a software engineering role, not a traditional manual QA position. You will write code most days and own the verification and release system that carries every build from merge to customer. Roughly 70% of the role is AI-powered verification through agent-run test harnesses, LLM graders, regression coverage, flake management, and automated release gates. Roughly 30% is release and environment engineering across CI health, artifact publication, deployment pipelines, and reliable demo and staging environments.
You will eliminate silent skips, build fresh-install and upgrade verification, turn escaped bugs into permanent regression tests, expand natural-language UAT executed by coding agents, own release candidates and artifact publication, automate credentials and certificates, and make release readiness visible through trusted system evidence.
• 7 to 15 years in quality engineering, release engineering, platform engineering, developer productivity, SDET-adjacent engineering, or a similar software role.
• Production-quality Python and strong software engineering fundamentals.
• Deep fluency with GitHub Actions or an equivalent CI system.
• Genuine interest and practical judgment in LLM-driven and agent-driven verification.
• Experience with Docker, Kubernetes, Helm, AWS, cloud deployment mechanics, secrets, credentials, and certificates.
• High ownership and clear technical communication through runbooks, dashboards, retrospectives, and operating policies.
• Full work authorization in either the United States or Canada. Visa sponsorship and transfer support are not available.
Nice to have: TypeScript, Snowflake Native Apps, Playwright, LLM-as-judge or grader design, nondeterministic system testing, and early-stage startup quality infrastructure.
• $170,000 to $200,000 base salary, based on qualifications and experience.
• Competitive equity and benefits.
• Remote-first across the United States and Canada.
• Periodic team offsites and flexible hybrid access to the New York City office for local team members.
• High ownership over a founding technical function at a $5M-funded enterprise AI company.
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