AI Full stack Lead Engineer

Ryan Specialty; Mumbai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Ryan Specialty seeks an AI Full Stack Engineer to design, build, and deploy production-grade web apps powered by AI tools, LLMs, and autonomous AI agents. You will craft end-to-end solutions—from AI-backed backends and APIs to responsive frontends using React/Next.js.

You'll implement RAG pipelines, work with vector databases, and leverage tools like Copilot and Claude Code. Deployment to Azure/AWS with Docker/Kubernetes is required, along with CI/CD and ongoing model improvement.

Qualifications

• Experience building or integrating AI Agents with LangChain or similar.
• Proficiency with LLM APIs: OpenAI, Azure OpenAI, Anthropic, or Gemini.
• Strong understanding of RAG pipelines, vector embeddings, and semantic search.
• Experience with Docker and cloud deployment (Azure or AWS).
• Experience with relational and NoSQL databases (PostgreSQL, MongoDB, Redis).

Responsibilities

• Design and develop full-stack AI-powered applications.
• Integrate LLM APIs into frontend and backend layers.
• Develop RESTful and GraphQL APIs for AI agents.
• Containerize and deploy to Azure/AWS with CI/CD.
• Collaborate with product, data and DevOps teams to ship features.

Skills

LangChain

LangGraph

AutoGen

CrewAI

LLM APIs

REST APIs

React/Next.js

Kubernetes

Docker

Azure

AWS

PostgreSQL

MongoDB

Redis

Semantic search

Tools

Docker

Kubernetes

Azure

AWS

PostgreSQL

MongoDB

Redis

React

Next.js

Job description

We are looking for an AI Full Stack Engineer who can build complete, production-grade web applications powered by AI tools, LLMs, and autonomous AI Agents. You will design, develop, and deploy end-to-end solutions — from intelligent backend services and AI-driven APIs to polished, interactive frontends — leveraging the latest AI development platforms and agentic frameworks

Key Responsibilities

• Design and develop full stack applications with AI-native features, integrating LLM APIs (OpenAI, Azure OpenAI, Anthropic Claude) into both frontend and backend layers
• Develop RESTful and GraphQL APIs that expose AI agent capabilities to frontend clients and third-party systems
• Build responsive, modern UIs using React / Next.js that interact with AI backends in real-time (streaming responses, tool call results, agent progress)
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases (Azure AI Search) for contextual AI applications
• Leverage AI coding assistants (GitHub Copilot, Cursor, Claude Code) as core development tools to accelerate full-cycle engineering work
• Containerize and deploy full stack AI applications to Azure / AWS using Docker, Kubernetes, and cloud-native CI/CD pipelines
• Monitor, evaluate, and improve LLM-powered features through prompt engineering, fine-tuning, and feedback loops
• Collaborate with product, data, and DevOps teams to ship AI-powered features from prototype to production

Required Skills

• Hands-on experience building or integrating AI Agents with frameworks like LangChain, LangGraph, AutoGen, or CrewAI
• Experience calling and fine-tuning LLM APIs — OpenAI, Azure OpenAI, Anthropic, or Gemini
• Solid understanding of RAG pipelines, vector embeddings, and semantic search
• Proficiency with containerization (Docker) and cloud deployment (Azure or AWS)
• Experience with relational and NoSQL databases (PostgreSQL, MongoDB, Redis)
• Familiarity with REST API design and integration patterns
• Comfort using AI-assisted development tools (Copilot, Cursor, Claude Code) as day-to-day workflow

Nice to Have

• Experience with Azure AI Foundry, Azure Machine Learning, or AWS Bedrock
• Knowledge of MLOps practices and model monitoring
• Exposure to multi-modal AI applications (vision, speech, document intelligence)
• Understanding of prompt engineering strategies, chain-of-thought, and function calling
• Contributions to open-source AI/agent projects