Lead AI Data Engineer

EXL; Dadri; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

EXL is seeking a Solution Architecture & Technical Leadership expert to architect enterprise-grade GenAI solutions and lead AI delivery across multiple projects. You will set design patterns, governance, and best practices for agentic systems and RAG pipelines.

You will mentor engineers, conduct architecture reviews, and collaborate with data engineering to ensure scalable, high-performance implementations while shaping EXL’s GenAI strategy and technology choices.

Qualifications

• 9-12 years total experience
• 2-4+ years hands-on in LLM / GenAI delivery (production use cases)

Responsibilities

• Solution Architecture & Technical Leadership
• Architect enterprise-grade agentic and LLM solutions (single-agent, multi-agent, tool-driven workflows)
• Define scalable GenAI system design patterns (RAG, orchestration layers, evaluation frameworks)
• Act as the technical anchor for GenAI initiatives across projects
• Drive design reviews, architecture governance, and best practices
• Agentic AI & LLM Engineering
• Design and build agentic systems using LLMs for use cases such as: Knowledge assistants
• Workflow orchestration
• Implement advanced prompt engineering strategies, prompt orchestration, and reasoning chains
• Build tool-calling / function-calling frameworks for agent workflows
• RAG & Retrieval Systems
• Lead end-to-end implementation of RAG pipelines: Data ingestion to embeddings to vector indexing to retrieval to response generation
• Optimise retrieval quality (recall, relevance, grounding)
• Evaluate and benchmark different architectures
• Productisation & Engineering Excellence
• 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)
• Governance, Safety & Evaluation
• Implement LLM guardrails: Hallucination control
• Safety filters
• Policy enforcement
• Define evaluation frameworks: Response quality metrics
• RAG benchmarking
• Human-in-the-loop validation
• Collaboration & Delivery Leadership
• Partner with Data Engineering to pipelines, data quality, governance
• MLOps to deployment, CI/CD, monitoring
• Business/Product to use-case alignment
• Drive end-to-end delivery ownership across multiple projects
• Technical Leadership Responsibilities (Critical Addition)
• Mentor and guide junior engineers and project teams
• Conduct technical reviews, solution walkthroughs, and code reviews
• Support pre-sales / RFPs / solution proposals with architecture inputs
• 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

Skills

LLMs

RAG pipelines

GPT + Agentic AI

LangChain/LangGraph

Agent orchestration

LLM evaluation

Python/PySpark

Data analysis

Databricks/Snowflake

Cloud platforms

SQL

DevOps/CI_CD

Data Engineering

NLP ML lifecycle

Analytics engineering

Solution design leadership

AI problem translation

Stakeholder comms

LoRA/PEFT

Azure AI stack

Security & privacy in GenAI

Autonomous agents

Education

9-12 years total experience

2-4+ years hands-on in LLM / GenAI

Tools

FastAPI

Flask

LangChain

Job description

Solution Architecture & Technical Leadership

• Solution Architecture & Technical Leadership
• Architect enterprise-grade agentic and LLM solutions (single-agent, multi-agent, tool-driven workflows)
• Act as the technical anchor for GenAI initiatives across projects
• Drive design reviews, architecture governance, and best practices
• Agentic AI & LLM Engineering
• Design and build agentic systems using LLMs for use cases such as: - Knowledge assistants
• Workflow orchestration
• Implement advanced prompt engineering strategies, prompt orchestration, and reasoning chains
• Build tool-calling / function-calling frameworks for agent workflows
• RAG & Retrieval Systems
• Optimise retrieval quality (recall, relevance, grounding)
• Evaluate and benchmark different architectures
• Drive code quality, testing standards, and reusable architecture components
• Ensure solutions are performance optimised (latency, cost, reliability)
• Governance, Safety & Evaluation
• Implement LLM guardrails: - Hallucination control
• Safety filters
• Policy enforcement
• Collaboration & Delivery Leadership
• Partner with: - Data Engineering to pipelines, data quality, governance
• Drive end-to-end delivery ownership across multiple projects
• Technical Leadership Responsibilities (Critical Addition)
• Mentor and guide junior engineers and project teams
• Conduct technical reviews, solution walkthroughs, and code reviews
• Support pre-sales / RFPs / solution proposals with architecture inputs
• 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

Key Responsibilities

• Solution Architecture & Technical Leadership
• Architect enterprise-grade agentic and LLM solutions (single-agent, multi-agent, tool-driven workflows)
• Define scalable GenAI system design patterns (RAG, orchestration layers, evaluation frameworks)
• Act as the technical anchor for GenAI initiatives across projects
• Drive design reviews, architecture governance, and best practices
• Agentic AI & LLM Engineering
• Design and build agentic systems using LLMs for use cases such as: - Knowledge assistants
• Document automation & intelligence
• Workflow orchestration
• Implement advanced prompt engineering strategies, prompt orchestration, and reasoning chains
• Build tool-calling / function-calling frameworks for agent workflows
• RAG & Retrieval Systems
• Lead end-to-end implementation of RAG pipelines: - Data ingestion to chunking to embeddings to vector indexing to retrieval to response generation
• Optimise retrieval quality (recall, relevance, grounding)
• Evaluate and benchmark different architectures
• Productisation & Engineering Excellence
• 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)
• Governance, Safety & Evaluation
• Implement LLM guardrails: - Hallucination control
• Safety filters
• Policy enforcement
• Define evaluation frameworks: - Response quality metrics
• RAG benchmarking
• Human-in-the-loop validation
• Collaboration & Delivery Leadership
• Partner with: - Data Engineering to pipelines, data quality, governance
• MLOps to deployment, CI/CD, monitoring
• Business/Product to use-case alignment
• Drive end-to-end delivery ownership across multiple projects
• Technical Leadership Responsibilities (Critical Addition)
• Mentor and guide junior engineers and project teams
• Conduct technical reviews, solution walkthroughs, and code reviews
• Support pre-sales / RFPs / solution proposals with architecture inputs
• 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

Must-Have Skills

• 9-12 years total experience
• 2-4+ years hands-on in LLM / GenAI delivery (production use cases)

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.)
• RAG pipelines and retrieval optimisation
• 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

Core Engineering

• Strong 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)

• Data Engineering (ETL/ELT, pipelines, orchestration)
• Data Science / ML lifecycle (especially NLP)
• Analytics engineering / data products

Leadership Capabilities

• Experience leading solution design or small teams
• Ability to translate business problems into AI solutions
• Strong stakeholder communication and influencing skills

Good-to-Have / Preferred

• Fine-tuning approaches: LoRA / PEFT / prompt tuning
• 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)