Build and own evaluation infrastructure for AI agents, including CI/CD pipelines, scorers, datasets, annotation workflows, observability tools, and diagnostic systems. Run experiments across prompts, models, and agent harnesses to improve quality, latency, and cost. Lead the AI Quality engineering team while remaining hands-on, partnering closely with AI Core engineering to validate production improvements.