Python GenAI Solution Architect

Epam Systems; Hyderabad, Gurugram District, Bengaluru; Hybrid; INR 4,000,000 - 8,000,000; Full time

Job summary

Epam Systems in Hyderabad seeks an experienced software engineer to design and deploy scalable Generative AI apps and agentic solutions. You will build AI agents using LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Copilot Studio, and develop robust back-end services and data pipelines.

You will advance RAG-based patterns, prompt engineering, and agent workflows while integrating LLMs with enterprise systems.

Qualifications

• 10+ years of overall software engineering experience.
• 3+ years of hands-on experience building applications using Generative AI and LLM technologies.
• Strong proficiency in Python and backend development for production-grade apps.
• Experience with agentic AI frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Copilot extensibility.
• Solid backend skills including REST/gRPC APIs, asynchronous programming, Docker, and FastAPI/Flask.
• Expertise with leading LLMs (OpenAI GPT, Claude, Gemini) and open-source options.
• Experience with RAG and vector databases (Pinecone, Weaviate, ChromaDB, Qdrant).
• Proficiency in prompt engineering, LLM orchestration, guardrails, and ReAct patterns.
• Strong problem-solving, system design, and architectural decision-making.
• Excellent communication for collaboration across global teams.

Responsibilities

• Design and develop scalable Generative AI applications and agentic solutions.
• Build and orchestrate AI agents using LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Copilot Studio.
• Develop and maintain backend services, APIs, microservices, and data pipelines.
• Implement advanced AI patterns including RAG, Agentic RAG, tool calling, planning loops, and human-in-the-loop workflows.
• Engineer and optimize prompts, system instructions, and agent workflows.
• Integrate LLMs with enterprise systems and third-party APIs.
• Monitor and improve model/agent performance with observability tools and feedback.
• Collaborate with Product, Engineering, Data, and Design teams.
• Stay updated with AI tech and contribute innovative ideas.

Skills

10+ years software engineering

Generative AI/LLM

Python proficiency

Backend design

Problem solving

Communication

System design

Tools

LangChain

LangGraph

Google ADK

CrewAI

AutoGen

Microsoft Copilot Studio

Job description

Role & responsibilities

Design, architect, and develop scalable Generative AI applications and agentic solutions for real-world business use cases.

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

Develop and maintain backend services, APIs, microservices, and data pipelines that power AI-driven products.

Implement advanced AI patterns including RAG, Agentic RAG, tool/function calling, planning & reflection loops, and human-in-the-loop workflows.

Engineer and optimize prompts, system instructions, and agent workflows to improve reliability, accuracy, and user experience.

Integrate LLMs with enterprise systems, third-party APIs, vector databases, and knowledge repositories.

Monitor, evaluate, and continuously improve model and agent performance using observability tools, metrics, and user feedback.

Collaborate closely with Product, Engineering, Data, and Design teams to deliver impactful AI solutions.

Stay current with emerging AI technologies, frameworks, and best practices, contributing innovative ideas to the team.

Document architectures, design decisions, and reusable solution patterns while supporting knowledge sharing across teams.

Preferred candidate profile

• 10+ years of overall software engineering experience
• 3+ years of hands-on experience building applications using Generative AI and LLM technologies.
• Strong proficiency in Python and experience developing production-ready applications.
• 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 skills, including REST/gRPC APIs, asynchronous programming, Docker, and frameworks such as FastAPI or Flask.
• Solid understanding of leading LLMs including OpenAI GPT models, Anthropic Claude, Google Gemini, and open-source alternatives.
• Practical experience building RAG solutions using vector databases such as Pinecone, Weaviate, ChromaDB, or Qdrant.
• Expertise in prompt engineering, LLM orchestration, structured outputs, guardrails, ReAct patterns, and evaluation techniques.
• Strong problem-solving, system design, and architectural decision-making skills.
• Excellent communication skills with the ability to collaborate effectively across global teams.

Preferred Qualifications

• Experience with AI observability and evaluation tools such as LangSmith, Ragas, DeepEval, Arize, or Weights & Biases.
• Familiarity with model adaptation and fine-tuning techniques (LoRA, PEFT, RLHF concepts).
• Experience with cloud AI platforms including Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Understanding of CI/CD, MLOps, and LLMOps practices.
• Exposure to graph databases, knowledge graphs, and structured data integration.
• Experience with event-driven architectures and messaging platforms such as Kafka or RabbitMQ.