Senior AI Quality Engineer (LLM Evaluation & Automation) 1754
This is a remote position. Owns the eval harness and quality gate from the beginning. This role replaces the old late-stage “Evals Specialist” model with a standing owner for measurable agent quality.
Key Responsibilities
- Build and maintain the MVP eval harness: golden tasks, exception tasks, scorecard metrics, and regression packs.
- Wire evals into CI so quality regressions fail builds and releases.
- Define and maintain release-gate thresholds with Product and the Tech Lead.
- Lay the path for later adversarial and drift-testing expansion without overbuilding MVP scope.
Requisitos Must-Have Qualifications
- Experience evaluating ML, LLM, or non-deterministic systems.
- Strong test and benchmark design capability.
- Comfort working with noisy metrics, thresholds, and probabilistic behavior.
- Good scripting and automation skills.
AI-First Expectations
- Uses AI to generate candidate eval cases and failure hypotheses, but never confuses generated tests with validated quality.
- Approaches AI quality as an operating system, not a QA afterthought.
What Success Looks Like in the First 90 Days
- The first reference agent has a published scorecard and gated eval path.
- Golden and exception tests run automatically.
- The team can explain what “good enough to ship” means in measurable terms.