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The role keeps production AI services running, covering model deployment, inference serving, monitoring, release automation, and cost and performance work. It works across AI engineering, cloud, and application teams. Candidates need Python, containers, CI/CD, and production troubleshooting skills, with MLOps and LLM or GPU serving experience as a plus.