Full Stack Engineer

The Full Stack Engineer is responsible for designing, developing, deploying, and maintaining scalable, high-performance, and secure web applications. The role requires strong software engineering fundamentals and experience delivering digital and AI-enabled products. Engineers must work in an agile, DevOps-driven environment, contributing to the development, deployment, and scaling of these products while ensuring high software quality, maintainability, security, and continuous improvement.

Key Responsibilities:

• Take full ownership of end-to-end application development, integrating frontend, backend, cloud infrastructure, and AI services.
• Design, develop, and maintain responsive, accessible, and performant web applications.
• Implement modern frontend architectures, ensuring reusability, scalability, and security.
• Develop backend services and APIs, ensuring reliability, security, and observability.
• Ensure adequate automated test coverage and proactively fix bugs and defects.
• Optimize CI/CD deployment strategies, ensuring seamless and automated releases.
• Automate infrastructure provisioning, monitoring, and cloud deployments using DevOps best practices.
• Ensure application security, including authentication, authorization, API security, and frontend security best practices.
• Own the delivery, enhancement, and scaling of AI-enabled products in production.
• Continuously evaluate and adopt emerging technologies to improve application performance and developer productivity.

EXPERIENCE AND SKILLS NEEDED:

Full Stack Development:

• Degree or Diploma in Computer Science, Computer Engineering, Information Technology, or related disciplines.
• Experience with Git and modern branching workflows.
• Strong proficiency in both frontend and backend development.
• Experience delivering production-ready web applications and digital products across the full lifecycle, including development, testing, deployment, and production support.

Frontend Technologies:

• JavaScript and TypeScript.
• Frontend frameworks such as React.js and/or Next.js.
• Experience building responsive and user-centric web applications.
• Familiarity with UI component libraries such as Material-UI or Tailwind CSS.

Backend Technologies:

• Node.js (Express.js, NestJS) and/or Python (FastAPI, Flask, Django).
• Strong experience designing and developing RESTful APIs.
• Familiarity with GraphQL and WebSockets.
• Caching (e.g. Redis), API rate limiting, and scalability patterns (horizontal scaling, load balancing).
• Experience integrating with enterprise systems and third-party platforms.

AI Application Development:

• Hands-on experience building LLM-powered features in production, including retrieval-augmented generation (RAG), tool or function calling, and agent workflows.
• Experience implementing guardrails and evaluating LLM output quality.
• Proficient in using AI coding assistants with sound engineering discipline.

DevOps, Cloud, and Infrastructure:

• Experience with GitLab CI/CD pipelines and modern DevOps practices.
• Hands-on experience with AWS cloud services and architectures.
• Experience with containerisation technologies such as Docker.
• Familiarity with application monitoring and observability tools.

Security Best Practices:

• Awareness of LLM-specific risks such as prompt injection and sensitive data leakage (e.g. OWASP Top 10 for LLM Applications).
• Experience implementing authentication and authorisation mechanisms (OAuth, JWT).
• Knowledge of API security and secure coding practices.
• Familiarity with cloud security concepts and OWASP Top 10.

Software Quality & Testing:

• Experience with unit and integration testing.
• Experience with automated testing frameworks.
• Experience troubleshooting and resolving production issues.

Bonus Experience (Added Advantage):

• Experience delivering projects within the Singapore Government or Public Service sector.
• Familiarity with government security, governance, and compliance requirements.
• Experience with Microsoft Copilot, Azure OpenAI, or other enterprise AI platforms.
• Experience developing AI agents, copilots, chatbots, or workflow automation solutions.
• Familiarity with Kubernetes and container orchestration platforms.