Lead Engineer

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.
• Opportunity to shape the future of enterprise AI solutions
• Experience with retrieval augmented generation (RAG) algorithms for text summarization, question answering, etc.