Role: AI Full Stack Developer (GenAI / LLM Focus)

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Role Overview

We are seeking a hands-on AI Full Stack Developer to build and deliver end-to-end AI-powered applications that integrate LLM/GenAI capabilities into real-world business workflows.
This role is focused on AI-driven product development, combining backend services, frontend experiences, APIs, and intelligent workflows to create scalable and user-centric applications (e.g., chatbots, copilots, AI assistants).

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Key Responsibilities

• Build and deploy end-to-end AI applications (e.g., chatbot/copilot platforms) with UI, APIs, and backend services
• Design and develop REST APIs and services for LLM inference, prompt orchestration, and agent workflows
• Implement AI-driven user experiences, including:
  • Explainability features
  • Feedback loops
  • Human-in-the-loop (HITL) workflows
• Develop and manage prompt flows, tool/function calling, and agent orchestration
• Integrate AI/ML services with enterprise systems and external APIs
• Build React (or similar) based frontends to enable intuitive interaction with AI systems
• Ensure secure SDLC practices including code reviews, testing, dependency management, and vulnerability fixes
• Collaborate with architecture, platform, and product teams to align with enterprise standards
• Leverage AI coding tools (e.g., Copilot, agentic IDEs) to improve developer productivity

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Required Skills (Must-Have)

• 5+ years of full-stack software development experience
• Strong programming skills in Python (preferred) / Java / .NET
• Hands-on experience building LLM/GenAI-powered applications (production or strong POCs)
• Strong experience with:
  • REST API development
  • Backend service design and integration
  • Modern frontend frameworks (React preferred)
• Practical experience with:
  • LangChain / LangGraph / agent frameworks
  • Prompt engineering and prompt workflows
  • Tool/function calling and API orchestration
• Strong understanding of:
  • AI system design and application architecture
  • LLM integration patterns (RAG, agents, copilots)
• Experience with CI/CD, Git workflows, and automated testing

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Nice-to-Have (Highly Preferred)

• Experience building AI copilots, chatbots, or internal AI assistants
• Knowledge of AI observability and evaluation:
  • Prompt/version tracking
  • Model evaluation metrics
• Experience designing AI interaction UX (explainability, feedback, HITL)
• Exposure to LLM runtimes, embeddings, and vector databases