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