Job Description
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
- 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.
Required Technical Skills
Frontend
- 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.
Backend
- 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.
Databases
- Hands-on experience with MongoDB
- Experience with Cosmos DB
- Strong understanding of data modelling and database integration.
Generative AI / LLM
- 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.
Cloud & DevOps
- 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.
Agile & Engineering 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.
Preferred Experience
- 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.
Education
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent industry experience.