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About the role
Role: Agentic AI Lead (Data Engineering GenAI Transformation) We are seeking senior Data Engineering leaders who have evolved into handson GenAI / Agentic AI practitioners . This role is not for pure research, academic, or experimentation-focused profiles. The expectation is production-grade delivery , grounded in strong data engineering fundamentals and scaled enterprise systems. Key Responsibilities Lead Agentic AI Delivery at Enterprise Scale - Lead end-to-end architecture, design, and production deployment of Agentic AI solutions for complex enterprise and Life Sciences use cases - Build, deploy, and optimize multi-agent systems involving planning, reasoning, orchestration, tool usage, and memory management - Drive GenAI implementations beyond POCs into secure, scalable, and observable production systems Must-Have Profile : Core Background - 12+ years of experience with a strong foundation in Data Engineering , evolving into AI / GenAI delivery roles - Proven experience delivering production-grade GenAI / Agentic AI solutions in real enterprise environments Data Engineering Excellence - Deep expertise in Databricks (PySpark, Delta Lake, workflows, optimization) - Extensive experience designing, building, and scaling ETL pipelines (batch and streaming) - Strong programming skills in Python and SQL - Hands-on experience with cloud platforms (AWS, Azure, or GCP) Agentic AI & GenAI Capabilities - Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or equivalent - Real-world implementation of multi-agent systems and autonomous workflows - Experience building RAG-based, tool-integrated AI solutions - Practical knowledge of model fine-tuning / adaptation techniques - Strong understanding of: - Prompt engineering - LLM orchestration and tool usage - Memory handling, agent context, and workflow optimization .
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