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 :

1. Prompt engineering.

2. LLM orchestration and tool usage.

3. Memory handling, agent context, and workflow optimization.