Test automation and performance testing are in scope, but the center of gravity is evaluating non-deterministic systems, where the same input produces different outputs, "correct" is often fuzzy, and failure modes such as hallucination, grounding failure, drift, and prompt injection are ones no assertion library catches. Our squads are small and senior, and we need someone who owns how the organization knows its AI systems work - evaluation across assistants, retrieval pipelines, agent workflows, voice and document systems, and the infrastructure that turns "it seems better" into evidence someone can act on.