Lead AI Data Engineer

ExlService Holdings, Inc.; Gurgaon; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

ExlService Holdings, Inc. seeks a senior GenAI Leader to architect and guide enterprise agentic AI initiatives in Gurgaon. You will own system design patterns, governance, and risk controls while steering multiple delivery teams and collaborating with data, MLops, and product stakeholders.

Experts with 9–12 years of experience in LLM/GenAI delivery, strong Python, and data engineering skills will thrive in this role. On-site engagement in Gurgaon is expected.

Qualifications

• Extensive experience delivering GenAI/LLM solutions in production.
• Strong architecture, governance, and design-review capabilities.
• Proven ability to lead multi-project programs and mentor teams.

Responsibilities

• Lead solution architecture for enterprise GenAI initiatives across projects.
• Drive end-to-end delivery, governance, and performance optimization.
• Mentor engineers and contribute to pre-sales and proposals.

Skills

GenAI delivery leadership

Agentic AI

Python programming

Data engineering

Leadership & mentoring

Education

Bachelor's degree in CS/Engineering

Tools

LangChain

LangGraph

Azure Databricks

Snowflake

Job description

Key Responsibilities

1. 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

2. 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

3. RAG & Retrieval Systems

• Lead end‑to‑end implementation of RAG pipelines:
  • Data ingestion → chunking → embeddings → vector indexing → retrieval → response generation
• Optimise retrieval quality (recall, relevance, grounding)
• Evaluate and benchmark different architectures

4. 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)

5. 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

6. Collaboration & Delivery Leadership

• Partner with:
  • Data Engineering → pipelines, data quality, governance
  • MLOps → deployment, CI/CD, monitoring
  • Business/Product → use‑case alignment
• Drive end‑to‑end delivery ownership across multiple projects

7. 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

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)

Prior experience in one or more:

• 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)