Full Stack Developer

Role Overview

We are looking for a hands-on Full Stack Developer with strong experience in modern frontend development using React.js, backend development using Python, and practical exposure to LLM-based applications and agentic workflows.

Key Responsibilities

• Develop responsive and user-friendly web applications using React.js.
• Build reusable UI components, dashboards, forms, and workflow interfaces.
• Design and develop scalable backend services and REST APIs using Python.
• Integrate applications with third-party platforms and APIs.
• Develop LLM-powered capabilities such as conversational interfaces, summarisation, recommendations, and intelligent automation.
• Build agentic workflows involving tool calling, orchestration, state management, validations, guardrails, and human-in-the-loop processes.
• Design data models and work with relational and vector databases.
• Write clean, maintainable, secure, and testable code.
• Participate in technical design, code reviews, sprint delivery, testing, deployment, and production support.

Mandatory Skills

• 6 to 12 years of full-stack application development experience.
• Strong hands-on experience with React.js, JavaScript/TypeScript, HTML5 and CSS3.
• Experience with React hooks, state management, responsive design and API integration.
• Strong backend development experience using Python.
• Experience with FastAPI, Django, Flask or an equivalent framework.
• Good understanding of REST APIs, authentication and authorization.
• Experience with PostgreSQL, MySQL or another relational database.
• Understanding of prompt engineering, embeddings, vector databases and RAG.
• Experience with agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen or CrewAI.
• Working knowledge of Git, Docker, CI/CD, application logging and testing.

Preferred Skills

• Experience with Next.js, Tailwind CSS, Material UI, Redux Toolkit or Zustand.
• Familiarity with WebSockets, background processing, queues and event-driven architectures.
• Understanding of LLM evaluation, hallucination mitigation, observability, guardrails and cost optimisation.
• Exposure to AWS or Azure and container-based deployments.