Experience evaluating user-facing AI features in consumer applications, with an understanding of how technical metrics connect to user-perceived quality Familiarity with productivity software or creative tools, with the ability to assess output quality from a user workflow perspective Experience ensuring alignment between automated and human evaluation methods, including inter-annotator agreement analysis and bias detection Track record of designing evaluation systems that scale across multiple features or product areas without requiring bespoke solutions for each Experience evaluating different types of AI systems, including API-based and custom-trained models Demonstrated ability to communicate evaluation findings and readiness assessments to cross-functional partners Experience leveraging automation to scale evaluation data generation and analysis Experience building evaluation pipelines for conversational AI, dialogue systems, or agentic workflows, including turn-level and session-level automated scoring Familiarity with agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and observability tooling (LangSmith, Braintrust, Arize), with an understanding of how to instrument and evaluate multi-step agent runs Experience designing adversarial tests for tool-use reliability, function-calling accuracy, or agent planning quality Graduate degree in a relevant field