Brings strong product and technical fluency in applied AI, including LLM-based and agentic experiences, model selection, retrieval-augmented generation (RAG), tool and API orchestration, experimentation, and production AI constraints such as latency, cost, and safety, with deep expertise in evaluation frameworks. Agentic AI Testing - Experience testing AI agents that plan and take multi-step actions: task completion and tool-call accuracy metrics, trajectory review, simulated-user and scenario-based testing, and failure analysis for handoffs, escalations, and guardrail breaches.