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Nanyang Technological University

AI Engineer - Full Stack

Full-Stack EngineeringUpdated on Nov 14
Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

  • Around 2–3 years of full stack development experience, shipping production features in a modern web stack, such as TypeScript and React on the frontend, Python or Node.js on the backend, REST or GraphQL APIs, and SQL and/or NoSQL data stores.
  • Hands-on experience deploying applications on Google Cloud Platform and Amazon Web Services, including containerised workloads, managed services, and continuous integration and continuous delivery.
  • Demonstrated day-to-day use of AI tools such as Claude, Copilot, or Cursor for code generation, review, debugging, and documentation, with a clear understanding of their benefits and limitations.
  • Familiarity with data platform concepts, including pipelines, storage, metadata, catalogues, and access controls.
  • Working knowledge of AI and machine-learning evaluation, benchmarking, and/or data annotation workflows and related tools, such as evaluation harnesses and annotation platforms.
  • Strong communication skills and ability to work with technical and non-technical stakeholders across cultures and time zones.

Responsibilities

  • Design, build, and maintain full-stack data-platform modules, including frontend interfaces, backend services, APIs, and data models, supporting multimodal data collection, curation, and access.
  • Use AI tools deliberately for code generation, refactoring, code review, debugging, and documentation, and help the team codify good practices for AI-assisted development.
  • Write clean, well-tested, maintainable code; participate in code reviews and design discussions; and contribute to technical documentation for the platform.
  • Build features and tooling to 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 relevant evaluation frameworks, benchmark suites, and annotation tools, and help the team make build-versus-adopt decisions.
  • Deploy and maintain platform user interfaces and backend services on Google Cloud Platform and Amazon Web Services, including configuration, networking, and storage.
  • Set up and maintain continuous integration and continuous delivery 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.
  • Work 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 platform operations.

Desired Qualifications

  • Experience with multimodal data systems involving text, audio, images, or video.
  • Contributions to open-source AI or data tooling.
  • Experience operating within Singapore public-sector or research programmes.

About the Company

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