As a Senior / Lead AI Engineer, you will be responsible for architecting, developing, and deploying enterprise-scale AI solutions leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and Agentic AI frameworks. You will work closely with cross-functional teams to deliver innovative AI products while driving best practices in AI engineering, governance, and operational excellence.

Key Responsibilities

- Design, build, and deploy enterprise-grade LLM, Generative AI, and Agentic AI solutions.
- Lead the architecture and implementation of multi-agent systems and complex AI workflows.
- Build and optimize RAG (Retrieval Augmented Generation) architectures for enterprise use cases.
- Fine-tune, optimize, evaluate, and improve AI/GenAI models for performance, accuracy, scalability, and cost efficiency.
- Integrate AI solutions with cloud platforms, APIs, enterprise applications, and backend systems.
- Establish and maintain AI engineering best practices including AgentOps, governance, observability, security, and responsible AI principles.
- Implement automated deployment strategies using modern CI/CD pipelines.
- Collaborate with business stakeholders, architects, product teams, and engineering teams to ensure successful project delivery.
- Mentor and guide engineering teams on AI solution architecture and implementation.

Required Experience

- 2+ years of hands-on experience building and deploying LLM, GenAI, or Agentic AI solutions in production environments.
- Strong experience designing and implementing multi-agent frameworks and orchestration systems.
- Experience with AI-assisted software development tools such as:

- GitHub Copilot

- Claude Code

- Codex

- Similar AI SDLC tools




- Strong expertise in RAG architecture design and implementation.
- Experience optimizing AI models, prompts, workflows, and inference pipelines.
- Hands-on experience integrating AI applications with enterprise ecosystems and cloud services.

Technical Skills Programming & Frameworks

- Python
- LangChain
- LangGraph

Enterprise AI Platforms & Frameworks

- AgentBricks
- AgentCore (AWS)
- Microsoft Foundry
- Gemini Agent Studio
- Snowflake Cortex Agents

Cloud & AI Platforms

- AWS Bedrock
- Databricks Mosaic AI
- Microsoft Foundry
- Gemini Enterprise Agent Platform
- Snowflake Cortex

DevOps & Engineering

- Docker
- Kubernetes
- CI/CD Pipelines
- AI Governance
- MLOps / AgentOps best practices

Preferred Qualifications

- Experience in enterprise-scale AI transformation programs.
- Knowledge of Responsible AI, AI governance frameworks, and compliance standards.
- Experience leading technical teams and driving AI solution strategy.
- Exposure to observability, monitoring, evaluation frameworks, and AI platform engineering.

Soft Skills

- Excellent verbal and written communication skills.
- Strong stakeholder management and collaboration abilities.
- Ability to lead cross-functional teams and deliver business outcomes.
- Problem-solving mindset with a focus on innovation and continuous improvement.

Why EPAM?

- Work on cutting-edge AI and GenAI initiatives for global enterprises.
- Collaborate with highly skilled architects, engineers, and AI specialists.
- Exposure to large-scale digital transformation and innovation programs.
- Continuous learning opportunities through EPAM's world-class engineering culture.
- Prospect to shape the future of enterprise AI solutions
- Experience with retrieval augmented generation (RAG) algorithms for text summarization, question answering, etc.

📌 Lead Engineer (Chennai)
🏢 EPAM Systems
📍 Chennai