Sr/Lead Genai Engineer

Epam Systems; Bangalore Rural, Bengaluru; Hybrid; INR 4,800,000 - 7,500,000; Full time

Job summary

Epam Systems is seeking a Sr/Lead Python GenAI Engineer to design and deliver production-grade Generative AI and agentic solutions for enterprise use cases. You will guide engineering teams, implement RAG patterns, and integrate LLMs with enterprise APIs and data stores.

The role requires strong Python, backend, and microservices skills, plus hands-on experience with multiple AI frameworks and vector databases. Join a leadership-driven GenAI initiative.

Qualifications

• 5-12 years of overall software engineering experience.
• 3+ years of hands-on experience building Generative AI/LLM-based applications.
• Strong expertise in Python and production-grade software development.
• Hands-on experience with at least two Agentic AI frameworks, such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility.

Responsibilities

• Lead the design, development, and delivery of scalable Generative AI and Agentic AI applications.
• Design and implement AI agents, multi-agent systems, and agentic workflows for complex enterprise use cases.
• Build and orchestrate agents using LangChain, LangGraph, Google ADK, CrewAI, AutoGen, Microsoft Copilot extensibility, or similar frameworks.
• Develop production-grade Python applications, backend services, REST/gRPC APIs, microservices, and AI-driven data pipelines.
• Implement advanced GenAI patterns including RAG, Agentic RAG, tool/function calling, ReAct, planning, reflection, memory, and human-in-the-loop workflows.

Skills

Python

LLMs

RAG

AI agents

LangChain

LangGraph

REST APIs

Microservices

FastAPI/Flask

Tools

LangChain

LangGraph

Google ADK

CrewAI

AutoGen

Microsoft Copilot extensibility

Job description

Sr/Lead - Python GenAI Engineer

Experience: 5- 12 Years

Role: Sr / Lead AI Engineer

Role Overview:

We are looking for an experienced Sr/Python with design and development of production-grade Generative AI and Agentic AI solutions for enterprise use cases. The ideal candidate will have strong Python and software engineering fundamentals, hands-on experience with LLMs, RAG, AI agents, and multi-agent architectures, along with the ability to technically guide engineering teams.

Key Responsibilities:

- Lead the design, development, and delivery of scalable Generative AI and Agentic AI applications.

- Design and implement AI agents, multi-agent systems, and agentic workflows for complex enterprise use cases.

- Build and orchestrate agents using frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, Microsoft Copilot extensibility, or similar frameworks.

- Develop production-grade Python applications, backend services, REST/gRPC APIs, microservices, and AI-driven data pipelines.

- Implement advanced GenAI patterns including RAG, Agentic RAG, tool/function calling, ReAct, planning, reflection, memory, and human-in-the-loop workflows.

- Design prompt strategies, system instructions, structured outputs, guardrails, and evaluation mechanisms to improve LLM reliability and accuracy.

- Integrate LLMs with enterprise applications, APIs, vector databases, knowledge repositories, and external tools.

- Work with models such as OpenAI GPT, Anthropic Claude, Google Gemini, and open-source LLMs.

- Lead the development of scalable RAG solutions using Pinecone, Weaviate, ChromaDB, Qdrant, or equivalent vector databases.

- Implement AI observability, evaluation, monitoring, and continuous improvement using tools such as LangSmith, Ragas, DeepEval, Arize, or Weights & Biases.

- Provide technical leadership, code reviews, mentoring, and guidance to engineers working on GenAI solutions.

- Collaborate with Product, Engineering, Data, Cloud, and Architecture teams to translate business requirements into technical solutions.

- Establish reusable design patterns, development standards, and best practices for GenAI engineering.

- Contribute to technical documentation, architecture decisions, proof of concepts, and innovation initiatives.

- Stay current with emerging Agentic AI, LLM, GenAI frameworks, models, and enterprise AI technologies.

Required Qualifications :

Must Have :

- 512 years of overall software engineering experience.

- 3+ years of hands-on experience building Generative AI/LLM-based applications.

- Strong expertise in Python and production-grade software development.

- Hands-on experience with at least two Agentic AI frameworks, such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility.

- Strong backend development experience with FastAPI/Flask, REST/gRPC APIs, asynchronous programming, Docker, and microservices.

- Strong understanding of LLMs including OpenAI GPT, Anthropic Claude, Google Gemini, and open-source models.

- Hands-on experience designing and implementing RAG and Agentic RAG architectures.

- Experience with vector databases such as Pinecone, Weaviate, ChromaDB, or Qdrant.

- Strong knowledge of prompt engineering, tool/function calling, structured outputs, guardrails, ReAct, memory, and LLM evaluation.

- Strong understanding of system design, distributed systems, API architecture, and cloud-native development.

- Experience providing technical leadership and mentoring engineering teams.

- Strong analytical, problem-solving, communication, and stakeholder management skills.