Senior Full Stack Engineer

Job description / Role

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

Bachelors or masters degree in computer science, information technology, engineering, or a related discipline, or equivalent industry experience.