Python GenAI Engineer

Epam Systems; Hyderabad, Pune District, Bengaluru; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

Epam Systems is seeking a skilled Python GenAI developer to design and deploy production-grade GenAI applications. You will build agentic workflows with LangChain and LangGraph, design robust RAG pipelines, and seamlessly integrate LLMs with vector databases.

The role focuses on delivering scalable, production-ready AI solutions, leveraging OpenAI or other providers, and collaborating with cross-functional teams to ship high-impact AI capabilities.

Qualifications

• 4+ years Python development experience.
• Hands-on Generative AI / LLMs experience.
• Must have 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.

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.

Skills

Python

Generative AI

LangChain

LangGraph

RAG

LLM platforms

FastAPI

Flask

FAISS

Chroma

Pinecone

Weaviate

AI agents

Tools

Docker

Kubernetes

CI/CD

AWS

Azure

GCP

Job description

Required Skills & Qualifications

• Strong 4+ Years of experience in Pythondevelopment experience
• Hands-on experience withGenerative AI / LLMs
• Mandatory:LangChainandLangGraph
• Experience buildingRAGapplications
• 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

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