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 modern AI platforms - Azure AI, Azure OpenAI, OpenAI, Anthropic, or similar.

• Work on prompt design, response handling, and optimization 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 visualization 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 optimize 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.