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