AI Fullstack Developer

Deutsche Telekom Digital Labs; Gurugram District; On-site; INR 3,000,000 - 4,000,000; Full time

Job summary

Deutsche Telekom Digital Labs is seeking an experienced AI Full-stack Developer to design and deploy AI-powered applications with strong Python backend and React.js frontend expertise.

You will implement AI agents, integrate LLMs, and build scalable RAG pipelines, collaborating with product, UI/UX, and DevOps teams to deliver production-ready code.

Qualifications

• Strong backend development experience with Python frameworks (FastAPI/Flask/Django).
• Experience building AI-powered full-stack apps with React frontends.
• Proficiency in integrating LLMs and building RAG pipelines.
• Knowledge of LangChain and LangGraph for AI agent design.

Responsibilities

• Design, develop, and deploy AI-powered full-stack applications.
• Build backend services using Python (FastAPI/Flask/Django).
• Develop responsive frontend applications using React.js .
• Design and implement AI agents using LangChain and LangGraph.

Skills

Python

FastAPI/Flask/Django

React.js

LLM integration

RAG pipelines

Vector databases

LangChain

LangGraph

Multi-agent systems

API integration

Tools

OpenAI API

Anthropic API

Gemini API

Llama models

Job description

We are looking for an experienced AI Full-stack Developer to build and deploy next-generation AI-powered applications. The ideal candidate should have strong expertise in Python backend development, modern AI frameworks, LLM application development, and React.js for building intuitive user interfaces.

You will work on designing intelligent AI agents, integrating Large Language Models (LLMs), implementing RAG pipelines, and building scalable full-stack AI applications.

Responsibilities:

• Design, develop, and deploy AI-powered full-stack applications.
• Build backend services using Python (FastAPI/Flask/Django).
• Develop responsive frontend applications using React.js .
• Design and implement AI agents using LangChain and LangGraph.
• Integrate and optimize Large Language Models (OpenAI, Anthropic, Gemini, Llama, etc. ).
• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Implement Model Context Protocol (MCP) for tool integrations and agent orchestration.
• Develop multi-agent workflows and autonomous AI systems.
• Integrate external APIs, enterprise tools, and databases with AI agents.
• Optimize AI application performance, latency, and scalability.
• Collaborate with product managers, UI/UX designers, and DevOps teams.
• Write clean, maintainable, and production-ready code.
• Participate in architecture discussions, code reviews, and technical design.