Lead the architecture and implementation of scalable distributed systems powering AI features for millions of users. Build production infrastructure, data pipelines, and model-serving interfaces using Python, SQL, Spark or Dask, AWS, and Kubernetes. Partner with applied scientists to productionize ML and LLM features, own operational reliability and technical debt, respond to incidents, and mentor engineers while improving engineering practices across the AI Products team.