Experience architecting production Generative AI, retrieval-augmented generation, agentic AI, or multi-agent systems including modern AI architecture patterns including model selection and routing, embeddings, vector and enterprise search, context engineering, structured outputs, tool calling, orchestration, memory, state, and human-in-the-loop workflows. Experience with AI evaluation, observability, tracing, guardrails, model monitoring, Responsible AI, model governance, or production AI reliability and with traditional machine learning lifecycle capabilities including data pipelines, feature engineering, model serving, model registries, monitoring, and MLOps.