Design, build, and maintain scalable full-stack web applications using React and Node.js, integrating Generative AI/LLMs (RAG, LangChain, AI Agents). Develop APIs, containerized cloud deployments (Azure/AWS, Docker, Kubernetes), CI/CD pipelines, and enterprise AI workflows. Collaborate across product, architecture, DevOps, and business teams, participate in Agile ceremonies, and provide production support and performance optimization.
We are looking for an experienced Full Stack Engineer with strong hands-on expertise in React.js, Node.js, TypeScript/JavaScript, and Generative AI to design, develop, and deliver scalable enterprise applications and intelligent automation solutions.
The ideal candidate will have strong full-stack engineering capabilities combined with practical experience integrating Generative AI, Large Language Models (LLMs), RAG, AI Agents, and prompt engineering into production-ready applications.
You will work closely with product, engineering, architecture, DevOps, and business teams to build secure, scalable, cloud-native solutions and AI-powered enterprise workflows.
RequirementsKey Responsibilities
- Design, develop, and maintain scalable full-stack web applications using React.js and Node.js.
- Develop responsive, performant, and reusable frontend applications using React.js, JavaScript/TypeScript, and modern frontend development practices.
- Design and build scalable RESTful APIs, backend services, and microservices using Node.js and Express.js.
- Integrate enterprise applications with internal and external systems through APIs and modern integration patterns.
- Design and implement Generative AI solutions, intelligent automation workflows, and AI-powered applications.
- Integrate and work with modern LLM platforms including OpenAI, Azure OpenAI, and Google Gemini.
- Develop Retrieval-Augmented Generation (RAG) solutions and AI-powered knowledge applications.
- Design and implement AI Agents and agentic workflows for enterprise use cases.
- Apply prompt engineering techniques to improve the accuracy, reliability, and effectiveness of AI applications.
- Work with frameworks and technologies such as LangChain for LLM and AI application development.
- Integrate AI capabilities such as intelligent assistants, chatbots, document processing, automation, and other enterprise AI use cases.
- Design solutions that are scalable, secure, maintainable, and suitable for enterprise production environments.
- Deploy and manage applications across Azure and/or AWS cloud environments.
- Work with Docker and Kubernetes for containerization and cloud-native application deployment.
- Contribute to CI/CD pipelines, automated deployments, and DevOps practices.
- Write clean, reusable, maintainable, and well-tested code following established engineering standards.
- Participate in code reviews, technical discussions, debugging, performance optimization, and production support.
- Collaborate with cross-functional teams to understand requirements and translate business needs into technical solutions.
- Participate in Agile delivery practices including sprint planning, daily stand-ups, backlog refinement, reviews, and retrospectives.
- Troubleshoot complex application, integration, and production issues and drive them through to resolution.
- Strong hands-on experience with React.js.
- Strong proficiency in JavaScript and/or TypeScript.
- Experience building responsive, reusable, and high-performance web applications.
- Strong understanding of modern React development and component-based architecture.
- Strong hands-on experience with Node.js.
- Strong experience with Express.js or similar Node.js frameworks.
- Experience developing scalable RESTful APIs and microservices.
- Strong understanding of API design, integration, authentication, and backend architecture.
- Hands-on experience with MongoDB.
- Experience with Cosmos DB.
- Strong understanding of data modelling and database integration.
- Practical hands-on experience implementing Generative AI solutions.
- Experience with one or more major LLM platforms:
- OpenAI
- Azure OpenAI
- Google Gemini
- Strong understanding of RAG (Retrieval-Augmented Generation) architectures.
- Hands-on experience with LangChain or similar LLM application frameworks.
- Experience building or integrating AI Agents / Agentic workflows.
- Strong understanding of Prompt Engineering and its application to real-world coding and enterprise AI use cases.
- Experience integrating LLM capabilities into applications through APIs/SDKs.
- Understanding of AI-powered automation and enterprise AI workflows.
- Hands-on experience with Azure and/or AWS.
- Experience with Docker and containerized application development.
- Experience with Kubernetes.
- Good understanding of CI/CD pipelines and DevOps practices.
- Experience with Git and modern source-control practices.
- Strong experience working in Agile/Scrum environments.
- Experience participating in sprint planning, stand-ups, backlog refinement, reviews, and retrospectives.
- Strong understanding of software development lifecycle and engineering best practices.
- Experience with code reviews, testing, debugging, performance optimization, and production support.
- Ability to work effectively with Product Owners, Architects, QA, DevOps, business stakeholders, and other engineering teams.
- Experience working on enterprise-scale applications or business platforms.
- Experience within banking, financial services, fintech, or other highly regulated environments.
- Experience implementing AI/GenAI solutions within enterprise environments.
- Experience with Azure OpenAI and enterprise Azure services.
- Experience integrating AI solutions with existing enterprise applications and APIs.
- Exposure to cloud-native and microservices architectures.
- Experience developing intelligent automation platforms, AI assistants, chatbots, or agent-based applications.
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent industry experience.
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