Lead/Architect - Genai

TymblHub; Pune District; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

EPAM Systems in Pune, India is seeking a GenAI Lead/Architect to spearhead the design and deployment of production-grade Generative AI and agentic AI solutions for enterprise use cases. You will guide engineering teams, implement RAG architectures, and integrate LLMs with enterprise systems.

Strong Python, backend, and cloud-native skills are essential. The role requires hands-on experience with LLMs, multi-agent frameworks, and scalable AI patterns, with a focus on reliability, observability,

Qualifications

• 8–16 years of overall software engineering experience.

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.

Skills

Python

Generative AI

LLMs

Agentic AI

Back-end development

System design

Tools

LangChain

LangGraph

Google ADK

CrewAI

AutoGen

Copilot extensibility

REST APIs

microservices

Job description

# Lead/Architect - GenaiEpam SystemsPosted on October 2, 2026---Experience8 - 13 yrsJob LocationPune, IndiaVacancy1DesignationLead ArchitectJob TypeNot specified---## Job Description**Vikram\\[e-mail] description** :Experience: 8 - 16 YearsRole: 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 :- 812 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.**Preferred Qualifications :**- Experience with LangSmith, Ragas, DeepEval, Arize, or Weights & Biases.- Experience with Azure OpenAI, AWS Bedrock, or Google Vertex AI.- Knowledge of LoRA, PEFT, fine-tuning, RLHF concepts, and model adaptation.- Understanding of LLMOps, MLOps, CI/CD, and AI governance.- Experience with knowledge graphs, graph databases, and structured data integration.- Experience with Kafka, RabbitMQ, or other event-driven architectures.- Experience building enterprise-scale AI platforms or reusable GenAI accelerators.Please share your resume and details to **Vikram\\[e-mail]****CTC :****Exp CTC :****Notice :****Available for F2F at Pune - EPAM office on 3rd Oct :****Regards,****Vikram K**