Python GenAI Engineer

Epam Systems; Jaipur; Hybrid; INR 1,000,000 - 1,500,000; Full time

Job summary

Epam Systems in Jaipur, India is seeking a Python GenAI engineer to develop scalable GenAI applications and deploy RAG pipelines.

The ideal candidate will have hands-on Python development, experience with LangChain and LangGraph, and familiarity with vector databases and ML model integration, including OpenAI/Azure OpenAI services. Join a fast-moving team building production-ready AI solutions.

Qualifications

• Proven Python development experience with hands-on GenAI/LLMs.
• Experience building and deploying RAG pipelines and integrating multiple LLM services.
• Hands-on experience with LangChain and LangGraph for agentic workflows.
• Knowledge of vector databases (FAISS, Chroma, Pinecone, Weaviate) and AI agents architectures.

Responsibilities

• Develop and deploy GenAI applications using Python.
• Build agentic workflows using LangChain and LangGraph.
• Design and optimize RAG pipelines for production use.
• Integrate LLMs and vector databases into scalable solutions.
• Deliver scalable, production-ready AI solutions.

Skills

Python development

Generative AI / LLMs

LangChain

LangGraph

RAG pipelines

LLMs integration

FastAPI/Flask

AI agents / multi-agent

Docker

Kubernetes

CI/CD

Tools

FAISS

Chroma

Pinecone

Weaviate

OpenAI APIs

Azure OpenAI

Claude

Gemini

FastAPI

Flask

Docker

Kubernetes

CI/CD

AWS

GCP

Job description

JD- Python GenAI Required Skills & Qualifications

• Strong Python development experience
• Hands-on experience with Generative AI / LLMs
• Mandatory: LangChain and LangGraph
• Experience building RAG applications
• Experience with OpenAI, Azure OpenAI, Claude, or Gemini
• FastAPI/Flask development experience
• Knowledge of vector databases (FAISS, Chroma, Pinecone, Weaviate)
• Understanding of AI Agents / Multi-Agent architectures
• Docker, Kubernetes, CI/CD

Nice to Have

• CrewAI, AutoGen, PydanticAI, Semantic Kernel
• AWS, Azure, or GCP
• Docker, Kubernetes, CI/CD

Responsibilities

• Develop and deploy GenAI applications using Python
• Build agentic workflows using LangChain and LangGraph
• Design and optimize RAG pipelines
• Integrate LLMs and vector databases
• Deliver scalable, production-ready AI solutions