Lead Full Stack AI Engineer (Agentic AI)

Lead Full Stack AI Engineer (Agentic AI)

Role Summary
We are seeking a Lead Full Stack AI Engineer with 10+ years of experience and strong hands-on expertise in React, Node.js, Python, and AI/ML technologies (RAG, LLMs, chatbots). The role requires building scalable full stack solutions, designing AI-driven capabilities, and leading delivery while working onsite with stakeholders and coordinating offshore teams.

Key Responsibilities

• Lead architecture design and end-to-end solution delivery with stakeholders
• Own technical decisions, standards, and reference implementations
• Develop full stack applications using React, Node.js, and Python
• Design scalable APIs and backend services for enterprise applications
• Implement micro-frontend architecture using Vite Module Federation
• Define host/remote structure, shared dependencies, and deployment strategy
• Enable single-origin application delivery using Nginx and routing patterns
• Design and build Agentic AI solutions using RAG, LLMs, and chatbots
• Develop prompt strategies and integrate AI services with enterprise APIs
• Build reusable services, accelerators, and solution templates
• Create library experiences for discoverable patterns from enterprise sources
• Lead offshore team delivery, sprint planning, and engineering governance
• Establish best practices across CI/CD, testing, release, and code quality

Required Skills & Experience

• 10+ years of full stack engineering experience with delivery ownership
• Expert in React, Node.js, and Python development
• Hands-on experience with RAG, LLMs, and chatbot implementations
• Strong understanding of API design, integration, and authentication patterns
• Experience with Module Federation (host, remotes, shared modules)
• Experience with Nginx-based deployments and production-ready architectures
• Strong stakeholder communication and onsite-offshore coordination

Nice to Have

• Experience with agentic workflows and orchestration patterns
• Exposure to enterprise AI tools and model selection considerations
• Experience building internal portals or reusable architecture libraries