(Summary generated by AI based on the full job description)
The project focuses on building production AI systems outside the notebook. Work covers creating knowledge-grounded AI, integrating LLMs into applications and operating classical ML models in cloud environments. Core technologies are Python, agent frameworks such as LangChain, LangGraph, Semantic Kernel, and vector databases with embeddings. Responsibilities include end-to-end pipelines: data ingestion, chunking, embeddings, retrieval and re-ranking, model serving and cost optimization on Azure/AWS/GCP, production-grade tested code, monitoring and drift detection, and collaboration with architects and data engineers.

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