Experience: 8-12 Years

Role: GenAI Lead /Architect

Role Overview:

We are looking for an experienced Python GenAI Lead to lead the 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:

- 8-12 years of overall software engineering experience.
- 3+ years of hands-on experience building Generative AI/LLM-based applications.
- Robust 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.
- Solid 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.

Please share your resume to [email protected]

CTC:

Exp CTC :

Notice :

Available for F2F at Pune - EPAM on 3rd Oct :

📌 Lead / Architect - Genai (Pune)
🏢 EPAM Systems
📍 Pune