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

* 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

Positive-to-Have / Preferred

📌 AI Data Engineer (Noida)
🏢 EXL
📍 Noida