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The ideal candidate will have strong data engineering foundations combined with expertise in Retrieval-Augmented Generation (RAG), agentic workflows, and AI service integration.\nResponsibilities\n1. Design and develop GenAI applications using Python and enterprise LLM platforms.\n2. Build scalable data pipelines for structured and unstructured data processing.\n3. Implement Retrieval-Augmented Generation (RAG) systems and vector-based search solutions.\n4. Integrate LLMs with enterprise applications through APIs and workflows.\n5. Develop cloud-native AI services on AWS, Azure, GCP, Databricks (DBRX), or Snowflake.\n6. Create agent-based solutions using LangChain and LangGraph.\n7. Ensure data quality, governance, and security compliance across AI workflows.\n8. 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