Description
GovTech is the lead agency driving Singapore's Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government's capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.
The AI Programme builds shared AI infrastructure that agencies can run in production, instead of rebuilding the same foundations independently. It sits within Government Digital Products, and it owns a small number of central products that a lot of other people's work now depends on.
Your responsibilities include:
- Building and running the surfaces officers use daily
- Building the runtime beneath them: tool orchestration, approval gates enforced in code, loop limits, per-turn tool filtering, memory and checkpointing, model routing and fallback
- Working on the platform half, where the job is to let other teams onboard their own agents, MCP servers, skills and models, with the policy checks and promotion workflows that let them move to production safely and repeatedly
- Extending the shared capability APIs (speech, vision, document extraction) and keeping them fast and cheap enough that agencies reach for them instead of building their own
- Integrating with what government already runs: identity, mail and calendar, document stores, agency line-of-business systems, the existing CI/CD pipelines
- Instrumenting the things you'll want to argue about later: tool call traces, latency, error taxonomies, cost per team and per feature
- Building evaluation into delivery, so changing a prompt, a tool or a model becomes a measurable decision instead of an argument
- Running it: deployments, incidents, capacity, cost, and the support queue of officers who found the case nobody thought of
You will thrive here if:
- You want the thing you wrote to be used by someone doing real work the next morning
- You're interested in what happens after launch, not only up to it
- The constraints (classification, audit trails, approvals, cost accountability) read to you as design problems rather than obstacles to route around
- You have a view on what belongs in a prompt and what belongs in the backend, and you'll defend it
- You'd rather ship something narrow and run it properly than demo something broad
- You use agentic coding tools every day and have opinions about where they help and where they quietly cost you
- You can talk to a policy officer in the morning and debug a streaming protocol after lunch
- You expect the model layer to change under you every few months, and you design so that's survivable
We're looking for someone with strong engineering fundamentals and fluency in TypeScript or Python. You should be comfortable moving across frontend, backend, data and cloud rather than settling into one layer. Experience with containers, CI/CD and infrastructure as code (Terraform or similar) is a plus.
In return, you can expect:
- Users from the first week, across agencies with genuinely different needs and maturity
- An unusual split, where you build the platform and also build on it, so you live with your own abstractions
- Ownership from design through operations, and the autonomy that has to come with it
- Work on production problems in agent systems: tool orchestration, governance, memory, evaluation and cost control under real audit and reliability constraints
- Colleagues across GovTech's AI Practice, Government Technology Office and product teams, and a mandate broad enough that good work travels
- Support to stay hands-on: learning budget, conferences, and time to go deep on the parts of this that nobody has settled yet