AI Engineer, Full Stack

Platform development and engineering

• Design, build, and maintain modules of the data platform across the full stack such as frontend interfaces, backend services, APIs, and data models to support multimodal data collection, curation, and access.
• Use AI tools (e.g. Claude, Copilot, Cursor) deliberately in your engineering workflow for code generation, refactoring, code review, debugging, and documentation and help the team codify good practices around AI-assisted development.
• Write clean, well-tested, maintainable code; participate in code reviews and design discussions; and contribute to the platform's technical documentation.

Domain workstreams: evaluations, benchmarks, and annotation

• Build features and tooling that support model and data evaluations, benchmark execution, and result tracking across the platform.
• Develop interfaces and workflows for data annotation used by internal teams and external community partners including task design, quality control, reviewer workflows, and progress tracking.
• Integrate with relevant evaluation frameworks, benchmark suites, and annotation tools, and help the team make sound build-vs-adopt decisions.

Infrastructure and deployment

• Deploy and maintain platform UI/UX and backend services on Google Cloud Platform (GCP) and Amazon Web Services (AWS), including configuration, networking, and storage.
• Set up and maintain CI/CD pipelines, monitoring, logging, and alerting to ensure reliability, performance, and security across environments.
• Manage cloud resources cost-effectively, and contribute to architecture decisions on scalability, multi-region considerations, and data residency.

Collaboration and delivery

• Work closely with the Project Manager, data engineers, researchers, and external partners to translate requirements into shippable features at a steady cadence.
• Participate in incident response, post-mortems, and continuous improvement of the platform's operations.

You should be a hands-on full stack engineer who is comfortable across frontend, backend, and cloud, and who actively uses AI tools to move faster and produce higher-quality work.

The ideal candidate would have:

• A degree in Computer Science, Information Technology, or equivalent.
• Around 2-3 years of full stack development experience, shipping production features in a modern web stack (e.g. TypeScript/React on the frontend; Python or Node.js on the backend; REST/GraphQL APIs; SQL and/or NoSQL data stores).
• Hands-on experience deploying applications on GCP and AWS, including containerised workloads, managed services, and CI/CD.
• Demonstrated use of AI tools (e.g. Claude, Copilot, Cursor) in your day-to-day engineering for code generation, review, debugging, and documentation with a clear sense of where they help and where they don't.
• Familiarity with data platform concepts: pipelines, storage, metadata, catalogues, and access controls.
• Working knowledge of AI/ML evaluation, benchmarking, and/or data annotation workflows, and the tooling ecosystem around them (e.g. evaluation harnesses, annotation platforms).
• Strong communication skills and the ability to work with both technical and non-technical stakeholders across cultures and time zones.
• Bonus: experience with multimodal data systems (text, audio, image, video); contributions to open-source AI/data tooling; experience operating within Singapore public sector or research programmes.

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU