AI Application Full-Stack Developer

As an AI Application Full-Stack Developer, you will develop modern web applications integrated with AI agents and cloud-native services. You will work across the entire stack—from frontend UI to backend APIs and databases—while collaborating closely with product, cloud, and AI engineering teams. This is a hands-on engineering role focused on delivering high-quality AI-powered applications. Key Responsibilities Full-Stack Development • Build responsive, high-quality frontend applications using React / Next.js /TypeScript. • Develop backend APIs and services using Python (FastAPI/Flask). • Implement authentication, authorization, data models, and API integrations. • Work with relational and NoSQL databases. AI Integration • Integrate applications with AI models, vector databases, and agent frameworks. • Implement workflows involving RAG, embeddings, conversational agents, or automation logic. • Work with cloud AI services (Google Cloud, AWS, Azure, or Vertex/Bedrock). System Implementation & Delivery • Translate requirements into technical tasks and features. • Ensure code is maintainable, well-structured, and well-tested. • Collaborate with UI/UX, AI engineers, and cloud engineers to ship features efficiently. • Participate in sprint discussions, reviews, and continuous improvement. Performance, Quality & Security • Apply best practices for security, scalability, performance, and reliability. • Implement logging, monitoring, and API performance optimisations. • Follow secure coding patterns and cloud-native development standards. Required Qualifications • Bachelor's or Master's degree in Computer Science or a related engineering field. • 7+ years of professional full-stack development experience. • Strong proficiency in: Javascript/TypeScript, React, and Next.js, Python (FastAPI or Flask) or any other backend programming language • Solid understanding of: REST API design Modern application architecture Databases (PostgreSQL, MySQL, MongoDB, etc.) Experience integrating with cloud services (GCP, AWS, or Azure). Familiarity with consuming AI APIs or building AI-powered features. Strong problem-solving skills and ability to work independently. Preferred Qualifications (Nice-to-Haves) • Experience working with RAG pipelines, vector DBs, or generative AI applications. • Familiarity with WebSockets, WebRTC, or real-time communication. • Basic understanding of CI/CD pipelines and DevOps fundamentals. • Experience with multi-tenant SaaS or enterprise-grade applications.