Full Stack Engineer (AI) - #1766

About the Role

We are looking for passionate and capable Full Stack Engineers to help build and enhance enterprise AI services used across the Singapore Public Service.

You will be part of a team supporting Whole-of-Government (WOG) AI platforms, including ChatGPT Enterprise, Microsoft 365 Copilot and Gemini Enterprise, as well as emerging AI-enabled applications and services.

You will focus on hands-on development and implementation of applications, APIs, integrations and automation solutions. You should be able to deliver assigned engineering tasks independently, troubleshoot common technical issues and contribute to production support under the guidance of the Engineering Manager/Technical Lead.

Prior experience with enterprise AI platforms or agentic AI is an advantage, but not a prerequisite. Candidates with solid full-stack engineering experience and a willingness to learn are encouraged to apply.

Key Responsibilities

1. Full Stack Development: Design, develop, test, deploy and maintain secure, scalable web applications, backend services, APIs and databases. Take ownership of solutions from development through production support.
2. Enterprise Integration: Build and maintain APIs and connectors integrating AI platforms with government identity services, enterprise applications, document repositories and existing systems.
3. AI Enablement and Workflow Automation: Develop automation for user provisioning, licence management and operational workflows. Support AI-powered applications, Model Context Protocol (MCP) integrations and agentic workflows with appropriate security and approval controls.
4. Cloud and DevOps Engineering: Implement and maintain CI/CD pipelines, automated testing, application monitoring and deployment processes. Troubleshoot production issues, optimise performance and improve application reliability.
5. Security and Compliance: Apply secure coding practices and implement authentication, authorisation, access controls, data protection and audit logging. Support security assessments, vulnerability remediation and compliance with applicable government security requirements.
6. Engineering Collaboration and Improvement: Collaborate with product managers, engineers, cybersecurity teams and government agencies to translate requirements into practical solutions. Participate in code reviews, technical documentation and continuous improvement, including the responsible use of AI-assisted development tools.

Requirements & Qualifications

A. Educational Qualification & Experience

Education

Degree or diploma in Computer Science, Software Engineering, Information Technology or a related discipline, or equivalent practical experience.

Experience

Relevant hands-on experience in full-stack software development, including building, deploying and maintaining applications in production environments.

Candidates should demonstrate practical engineering capabilities and experience delivering working software. Experience with enterprise AI platforms is advantageous but not mandatory.

B. Technical & Professional Competencies

Essential (Must-Have)

• Strong programming skills in at least one language such as TypeScript, JavaScript, Python, Java or C#.
• Hands-on experience with frontend frameworks such as React, Angular or Vue.js, and backend application development.
• Experience developing REST APIs and working with relational or NoSQL databases.
• Familiarity with Git, software testing, CI/CD and modern development practices.
• Understanding of application security, authentication, authorisation and secure data handling.
• Ability to troubleshoot application issues and support software through deployment and production operations.

Preferred (Advantageous)

• Experience with cloud platforms such as Microsoft Azure, AWS or Google Cloud, including containers or Infrastructure as Code.
• Experience integrating enterprise applications, Microsoft Graph APIs, Microsoft Entra ID or workflow automation systems.
• Exposure to generative AI, LLM APIs, tool calling, AI agents, retrieval-augmented generation (RAG) or Model Context Protocol (MCP).
• Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex or Cursor.
• Familiarity with application monitoring, observability and performance optimisation.
• Experience developing applications in enterprise, regulated or government environments.

C. Soft Skills & Communication Attributes

• Strong analytical, troubleshooting and problem-solving skills.
• Ability to take ownership of engineering deliverables from development through production support.
• Good written and verbal communication skills, with the ability to explain technical solutions to different stakeholders.
• Ability to work independently and collaborate effectively with multidisciplinary teams.
• Adaptability, willingness to learn and interest in emerging AI technologies.
• Commitment to software quality, security, reliability and continuous improvement.