Architect enterprise-grade agentic and LLM solutions (single-agent, multi-agent, tool-driven workflows)

Act as the technical anchor for GenAI initiatives across projects

Agentic AI & LLM Engineering

Document automation & intelligence

Build tool-calling / function-calling frameworks for agent workflows

Lead end-to-end implementation of RAG pipelines: - Data ingestion chunking embeddings vector indexing retrieval response generation

Optimise retrieval quality (recall, relevance, grounding)

Develop production-grade APIs/services (FastAPI, Flask, etc.)

Drive code quality, testing standards, and reusable architecture components

Ensure solutions are performance optimised (latency, cost, reliability)

Implement LLM guardrails: - Policy enforcement

Response quality metrics

Partner with: - Data Engineering pipelines, data quality, governance

MLOps deployment, CI/CD, monitoring

Drive end-to-end delivery ownership across multiple projects

Mentor and guide junior engineers and project teams

Drive reusable accelerators, frameworks, and COE assets

Stay ahead of industry evolution and help shape EXL's GenAI strategy

Influence technology choice, design decisions, and roadmap planning

Experience

9–12 years total experience

2–4+ years hands-on in LLM / GenAI delivery (production use cases)





LLM / GenAI & Agentic Engineering

Strong hands-on experience with: - LLMs (Claude, OpenAI, etc.)

GPT + Agentic AI implementation experience

Experience with: - LangChain, LangGraph, or similar frameworks

Agent orchestration and tool-calling architectures

Deep understanding of: - LLM limitations, evaluation, and optimisation strategies

Robust Python/Pyspark engineering expertise (production-grade development) with proven API integration experience

Deep data analysis experience and handling large volume of data

Fabric/Azure Databricks/Snowflake data engineering integration skills

Good exposure to: - Cloud platforms (Azure/AWS/GCP)

SQL

Containers, CI/CD, monitoring

Data / AI Foundations (Mandatory)

Prior Experience In One Or More

Data Engineering (ETL/ELT, pipelines, orchestration)

Data Science / ML lifecycle (especially NLP)

Analytics engineering / data products

Experience leading solution design or small teams

Ability to translate business problems into AI solutions

Experience with Azure AI stack (Azure OpenAI, AI Search)

Exposure to: - Enterprise security & data privacy in GenAI

Coding agents / autonomous agent frameworks

Experience in insurance / BFSI domains (valuable for EXL use cases)

📌 Lead AI Data Science Engineer (Pune)
🏢 EXL
📍 Pune