Generative AI & Model Engineering: Select, evaluate, and integrate foundation models on Amazon Bedrock; design, implement, and evaluate RAG pipelines (including retrieval quality and RAG evaluation); apply prompt engineering and model customization; and leverage Amazon SageMaker for building and deploying classical (non-generative) machine learning models and for the broader ML lifecycle - training, hosting, and monitoring - where appropriate. * Production Engineering & LLMOps: Operationalize AI agents end-to-end — automated AI agent evaluation, guardrails, observability, cost and latency optimization, CI/CD, and Infrastructure as Code (Terraform, CloudFormation, AWS CDK). Own the reliability, quality, and performance of deployed agents. * Strong proficiency in Python, together with solid software engineering practices (version control, testing, code review).
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