Description
Key Responsibilities
- Design and develop LLM-based applications using single-agent or simple multi-agent patterns for business use cases
- Build and maintain RAG pipelines: data ingestion → chunking → embeddings → retrieval → response generation
- Implement prompt engineering techniques (prompt templates, chaining, basic tool/function calling)
- Develop backend services/APIs for AI applications using Python frameworks (FastAPI / Flask / Streamlit)
- Integrate AI solutions with enterprise systems, databases, and APIs
- Apply basic guardrails and validation checks to improve response quality and reduce hallucination
- Work with Data Engineering teams to ensure data quality, pipeline efficiency, and proper documentation
- Collaborate with MLOps teams for deployment, monitoring, and iterative improvements
- Document solutions, reusable components, and best practices

Must-Have Skills

Experience
- 4–6 years total experience, with 1+ year hands-on experience in GenAI / LLM-based applications

LLM / GenAI & Agentic Engineering
- Solid 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 / Pref

📌 AI Data Engineer (Gurugram)
🏢 EXL
📍 Gurugram