Job Description

Key Responsibilities

  • Design and develop LLM-powered applications using agentic patterns (single/multi-agent) for business use cases
  • Build and optimise end-to-end RAG pipelines (ingestion, embeddings, retrieval, orchestration, response synthesis)
  • Implement prompt engineering and orchestration techniques (prompt chaining, tool/function calling, structured outputs)
  • Develop production-grade APIs and services (FastAPI/Flask/Streamlit) for GenAI applications
  • Integrate LLM solutions with enterprise systems, data platforms, and workflows
  • Apply guardrails and evaluation frameworks to improve response quality, reduce hallucinations, and ensure responsible AI usage
  • Collaborate with Data Engineering and MLOps teams for data pipelines, deployment, monitoring, and scaling
  • Contribute to reusable components, documentation, and engineering best practices

Experience & Core Requirements (Must-Have)

Overall Experience

  • 6–9 years total experience
  • 1–3+ years in hands-on GenAI / LLM application development (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

Good-to-Have / Preferred

  • Experience with fine-tuning techniques (LoRA, PEFT) or prompt tuning strategies
  • Experience with enterprise GenAI security & privacy practices (data masking, access control, compliance)
  • Familiarity with Azure AI ecosystem (Azure OpenAI, Azure AI Search, Fabric, etc.)

Exposure to agentic coding tools (e.g., Claude Code or similar environments)


Job Details

Role Level: Not Applicable Work Type: Full-Time
Country: India City: Gurugram ,Haryana
Company Website: http://www.exlservice.com Job Function: Data Science & AI
Company Industry/
Sector:
Business Consulting and Services

What We Offer


About the Company

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