Software Engineer - AI-enabled Products (National Environment Agency)

Learn more about GovTech at tech.gov.sg.

At National Environment Agency (NEA), we are always on the lookout for high performing individuals who share our aspiration of making Singapore one of the world’s best living environments.

The NEA is building AI products and shared platform capabilities that can improve how we run complex operational workflows.

We are hiring software engineers who can take ambiguous problems from brief to production. This is not a pure research role and not a demo-building role. The work is to build reliable, maintainable, policy-sensitive AI systems that can survive real users, real operational constraints, and public-sector trust requirements.

AI will support how we build. Engineers still own the design, judgement, quality, and consequences of what ships.

How we build

We prefer simple, durable engineering choices over novelty for its own sake. The stack may vary by product, but the principles do not: clear architecture, automated testing, CI/CD, observability, secure-by-design delivery, and systems that are easy to reason about after launch.

The team’s operating model is product-led and platform-amplified. Product squads prove value in real NEA’s workflows; shared platform capabilities make those products observable, testable, governable, and reusable across NEA. Engineers may work inside a product squad, on the shared AI platform, or in a forward-deployed model where they help a vertical team build AI capability before bringing reusable patterns back to the centre.

[What you will be working on]

-

Design, build, test, deploy, and operate AI-enabled products and platform components across NEA.

-

Work on areas such as LLM integration, agentic workflows, evaluation harnesses, observability, guardrails, model access, retrieval/memory patterns, and multimodal AI use cases.

-

Take ambiguous operations problems and turn them into maintainable software with clear success metrics.

-

Build production features for products such as automation, tools, assistants, and deterministic and agentic workflow.

-

Create engineering patterns that other product teams can reuse, including templates, playbooks, test harnesses, and reference implementations.

-

Work closely with product managers, designers, data scientists, governance colleagues, and business owners.

-

Use AI coding and development tools to accelerate delivery while retaining human accountability for design and quality.

-

Participate in design reviews, code reviews, incident response, and technical decision-making.

-

Push for root-cause fixes rather than surface-level patches.

[What we are looking for]

-

At least 3 years of relevant working experience in fields related to artificial intelligence, machine learning, data science, or software engineering.

-

Completed at least one hands-on AI development and deployment end-to-end project.

-

Strong software engineering fundamentals: system design, testing, version control, CI/CD, observability, security, and maintainable code.

-

Good engineering judgement: you can explain trade-offs clearly and defend a technical position without becoming attached to it.

-

Comfort with ambiguity: you can move from unclear policy, education, or operational needs into a working product shape.

-

Appetite for AI-native engineering: LLM applications, evaluation, agentic workflows, RAG/memory, multimodal models, or AI-assisted development.

-

Pragmatic taste in technology: you choose boring, durable tools when they are right, and newer AI tooling only when it genuinely improves the system.

-

Ownership mindset: you do not stop at prototype handoff; you care about deployment, monitoring, user feedback, and maintainability.

-

Ability to work with non-technical stakeholders in public-sector domains.

-

Bias for measurable quality: you care about evals, regression checks, traceability, and evidence before scaling.

Nice to have

-

Experience building production LLM or AI-enabled applications.

-

Experience with evaluation frameworks, prompt/context engineering, model monitoring, Langfuse/OpenTelemetry-style tracing, or AI safety guardrails.

-

Experience with Python, TypeScript, Go, PostgreSQL, containerised deployment, cloud services, or government/cloud-restricted environments.

-

Experience building internal platforms, developer tooling, or reusable engineering kits.

-

Familiarity with Environment Domain, public-sector operations, procurement, or high-trust digital services.

What success looks like

In the first 6 months, you should have shipped meaningful production work in at least one product or platform area, improved the team’s engineering quality bar, and helped convert one-off AI delivery into reusable capability. The best engineers in this role will not just “build features”; they will help define how NEA builds, evaluates, governs, and scales AI products.

Why this role matters

NEA’s AI work is moving beyond experiments. The next challenge is to make AI useful, safe, measurable, and maintainable across NEA workflows. This role is for engineers who want to build public-good AI systems with national-scale relevance, while shaping the operating model for how product teams use AI responsibly.

What we offer you:

GovTech is an equal opportunity employer committed to fostering an inclusive workplace that values diverse voices and perspectives, as we believe that diversity is the foundation to innovation.

Our employee benefits are based on a total rewards approach, offering a holistic and market-competitive suite of perks. These include leave benefits to meet your work-life needs and employee wellness programs.

We champion flexible work arrangements (subject to your job role) and trust that you will manage your own time to deliver your best, wherever you are, and whatever works best for you.

Learn more about life inside GovTech at go.gov.sg/GovTechCareers.

Stay connected with us on social media at go.gov.sg/ConnectWithGovTech