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About the Role

Build real-world AI-powered applications on top of modern AI services, with a strong web engineering foundation. Own end-to-end delivery - from requirement understanding to production deployment.

What You’ll Do

- Design and build AI-powered features and services integrated into web applications.
- Develop and integrate APIs using up-to-date AI platforms - Azure AI, Azure OpenAI, OpenAI, Anthropic, or similar.
- Work on prompt design, response handling, and optimisation of AI-driven workflows.
- Build scalable backend services using Python (FastAPI, Flask, or similar), APIs, and orchestration layers for AI-enabled application logic.
- Build frontend experiences for chat interfaces, AI workflows, and intelligent assistant features, including interactive dashboards and data visualisation UIs.
- Integrate AI responses into existing product workflows in a secure, scalable, and maintainable way.
- Architect clean, modular, and scalable backend and AI systems - including defining technical design, component boundaries, and integration patterns across the stack.
- Work with REST and GraphQL APIs for efficient data access and integration.
- Design and optimise database schemas across SQL and NoSQL.
- Write and maintain unit tests and integration tests; ensure high code quality through reviews and automation.
- Collaborate closely with product, design, and engineering teams, contributing to architecture discussions and technical decisions.

Must-Have Skills





- 5+ years of full-stack development experience, with at least 1 year of hands-on AI integration building production-grade AI applications (not just POCs).
- Expert in Python with backend frameworks (FastAPI, Flask, Django, or similar); solid grasp of REST and GraphQL API design.
- Strong database knowledge across SQL and NoSQL - PostgreSQL, MySQL, or SQL Server.
- Experience with Azure AI services, including Azure OpenAI and Cognitive Services; hands-on with LLM frameworks like LangChain or LlamaIndex, and agentic workflow orchestration using LangGraph.
- Experience building RAG (Retrieval-Augmented Generation) pipelines with vector databases like ChromaDB, Azure AI Search, or similar.
- Hands-on with both microservices and monolithic architectures.
- Testing proficiency with PyTest; API testing using Postman/Newman or similar.
- Frontend exposure with React.
- Familiarity with CI/CD pipelines, DevOps basics, cloud platforms, secure coding practices, and integration patterns.

Nice to Have

- Any Microsoft certification is an added value (e.g. Azure AI Engineer Associate, Azure Solutions Architect, or similar).
- Strong client communication skills - the ability to engage directly with stakeholders, translate technical concepts clearly, and represent the team in client-facing discussions.
- Hands-on experience shipping and maintaining AI features in real production environments, not only proof-of-concept or demo projects.

📌 AI Engineer with Fullstack for Bangalore (Bengaluru)
🏢 RECEX
📍 Bengaluru