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Job Description

Role : Agentic AI Lead (Data Engineering - GenAI Transformation).

Role Intent :

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 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.

- Architect and integrate Agentic AI systems with Databricks, data lakes, data warehouses, streaming platforms, and enterprise APIs.

- Design and optimize scalable ETL / ELT pipelines (batch and streaming) to power AI, ML, and GenAI workflows.

- Define architecture patterns, guardrails, and governance frameworks for enterprise Agentic AI.

- Partner with business stakeholders to identify high-impact AI use cases and mentor cross-functional teams.

Must-Have Profile :

- 12+ years of experience with a strong foundation in Data Engineering, evolving into AI / GenAI delivery roles.

- Deep expertise in Databricks (PySpark, Delta Lake, workflows, optimization).

- Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or equivalent.

- Real-world implementation of multi-agent systems and autonomous workflows.

- Strong programming skills in Python and SQL.

- Hands-on experience with cloud platforms (AWS, Azure, or GCP).

Skills That Give You an Edge :

- Experience with enterprise-scale AI transformations, preferably in Life Sciences / Pharma.

- Exposure to LLMOps / MLOps (monitoring, evaluation, governance, drift detection).

- Strong understanding of AI evaluation, guardrails, and Responsible AI practices.

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