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AI Summary
The role involves building and maintaining an MVP evaluation harness, including golden tasks and scorecard metrics. It also requires integrating evaluations into the CI pipeline to ensure quality regressions fail builds and releases.
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.
Requirements
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.
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