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. Originally posted on Himalayas