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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 hands‑on 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 stable, 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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