Full Stack Developer – AI/ML

Job Overview We are seeking a Full Stack Developer with AI/ML experience to design, develop, integrate, and maintain modern web applications with intelligent capabilities. Key Responsibilities Develop and maintain full-stack web applications across frontend, backend, databases, and APIs. Build and integrate AI/ML features such as chatbots, intelligent search, recommendations, personalisation, analytics, and automation. Develop REST APIs, microservices, and third-party integrations. Work with relational and NoSQL databases and support data integration. Deploy and support applications on AWS, Azure, or GCP. Participate in CI/CD, Docker, testing, monitoring, and performance optimisation. Apply secure coding, authentication, and data protection practices. Troubleshoot application, API, database, and deployment issues. Collaborate with product, AI/ML, DevOps, QA, and business teams to deliver solutions. Requirements Bachelor’s degree in Computer Science, IT, Software Engineering, or related field. 2–5 years of full-stack development experience. Strong experience with JavaScript/TypeScript and frameworks such as React, Angular, or Vue.js. Backend experience with Node.js, Python, Java, or Spring Boot. Experience with REST APIs, databases, and microservices. Practical experience with AI/ML development or AI service integration. Knowledge of Generative AI, LLMs, NLP, embeddings, or RAG is an advantage. Experience with AWS, Azure, or GCP and basic DevOps/CI/CD practices. Strong problem-solving, troubleshooting, communication, and teamwork skills. Technical Skills Frontend: React / Angular / Vue.js, JavaScript / TypeScript Backend: Node.js / Python / Java / Spring Boot Database: PostgreSQL / MySQL / MongoDB AI/ML: TensorFlow / PyTorch / Scikit-learn, AI APIs, GenAI/LLMs Cloud: AWS / Azure / GCP DevOps: Git, CI/CD, Docker; Kubernetes is an advantage Security: OAuth2, OpenID Connect, JWT Preferred Experience building AI-enabled enterprise applications. Experience with LLMs, RAG, NLP, or AI-powered search. Exposure to LMS, EdTech, or digital learning platforms. Experience with cloud-native applications and microservices.