The posting
Full Stack Engineer (AI Products & Platforms)
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.
- 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.



