Job Description

Key Responsibilities:

The Full-Stack Engineer will play a key role in developing and delivering innovative AI-powered digital services that enhance how users discover, access and interact with data. The role involves end-to-end development of public-facing applications, including AI chatbots, AI agents, Model Context Protocol (MCP) integrations and other AI-enabled data dissemination solutions.

Working in an agile and collaborative environment, the engineer will engage with internal stakeholders, cross-functional teams and technical teams to ensure seamless system integration and successful delivery of AI initiatives.

• Develop, deploy and maintain scalable, secure and high-performance AI-enabled web applications, including frontend interfaces, backend services and APIs hosted on cloud infrastructure.
• Develop AI-powered applications, including chatbots with session and context management, streaming responses and robust error-handling capabilities.
• Develop and integrate MCP servers and clients to enable AI agents and applications to securely access approved data, tools and internal or external services.
• Implement application and AI security controls, including authentication, authorization, access management, data protection and safeguards against AI-related vulnerabilities.
• Develop automated tests and evaluation processes for application functionality, AI chatbot responses, MCP integrations and interoperability to ensure system reliability and quality.
• Collaborate with DevOps and Quality Assurance (QA) teams to implement CI/CD pipelines, automate deployments and monitor application performance and availability.
• Monitor and optimize application performance, AI response quality, latency and resource utilization. Maintain technical documentation and evaluate emerging technologies where appropriate.

Experience and Skills Required

AI Technologies

• Hands-on experience integrating Large Language Model (LLM) APIs or SDKs (e.g. Amazon Bedrock, OpenAI, Anthropic or equivalent), including prompt management, structured outputs and tool/function calling.
• Hands-on experience developing MCP servers and integrating MCP clients using relevant SDKs, including tool definitions, resources (where applicable), access controls and schema validation.
• Experience with Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, embeddings, semantic or hybrid retrieval, and vector stores where appropriate.

Added Advantage:

• Hands-on experience developing and deploying AI agents using development frameworks (e.g. OpenAI Agents SDK or LangGraph) or managed platforms (e.g. Amazon Bedrock AgentCore), including workflow orchestration, tool integration, context and memory management, testing and monitoring.

Full-Stack Development

• Knowledge of computer science and software engineering principles, supported by a degree or diploma in Computer Science, Computer Engineering, Information Technology or a related discipline.
• At least 3 years of relevant working experience in software development or a related IT field.
• Good written and verbal communication skills, with the ability to collaborate effectively with technical teams and stakeholders.
• Experience in frontend and backend development using technologies such as JavaScript/TypeScript (React or Next.js) and Python (FastAPI) or Node.js, including responsive web application development and API integration.
• Experience designing and integrating APIs using REST, GraphQL or gRPC, as well as implementing real-time communication using WebSockets where required.
• Hands-on experience with AWS cloud services and containerised deployments (e.g. Docker), with knowledge of container orchestration (e.g. Kubernetes) and Infrastructure as Code (IaC) tools (e.g. Terraform or AWS CloudFormation).
• Experience implementing CI/CD pipelines (e.g. GitHub Actions or GitLab CI) and automated unit, integration and end-to-end testing for applications, APIs and AI/MCP workflows.
• Knowledge of application monitoring, logging and tracing, including AI service latency, API usage, tool-call failures and operational costs.
• Knowledge of backend scalability techniques, including caching, rate limiting, load balancing, autoscaling and performance optimisation.

Added Advantage:

• Familiarity with web analytics tools such as Whole-of-Government Application Analytics (WOGAA) or Google Analytics (GA) for monitoring website traffic, user behaviour and application usage to support performance analysis and continuous improvement.

Security Best Practices

• Knowledge of web application and cloud security practices, including Content Security Policy (CSP), secure Cross-Origin Resource Sharing (CORS) configuration, Cross-Site Scripting (XSS) prevention, OAuth 2.0/OpenID Connect, JSON Web Token (JWT) validation, Identity and Access Management (IAM), secrets management, encryption and relevant OWASP guidelines.
• Understanding of AI and MCP security risks, including prompt injection, sensitive data leakage and unauthorised tool execution, as well as appropriate mitigation measures such as least-privilege access controls and input/output validation.

Added Advantage:

• Knowledge of the Singapore Government Instruction Manual on Infocomm Technology and Smart Systems (ICT&SS) Management (IM8), including relevant security and data protection requirements.