[What the role is]

[What you will be working on]

Software Engineer, Systems team — Centre for Autonomous Mobility (CAM), Land Transport Authority. You will build the digital products that make safe autonomous vehicle deployments possible in Singapore, at scale. This role is open at two levels — a core set of responsibilities applies to all hires, with additional ownership and leadership expectations for more senior candidates (see section below).

CAM leads Singapore’s national effort to deploy autonomous vehicles (AVs) at scale safely. The Systems team builds the digital tools behind that mission — for instance, developing a monitoring system for AVs to collect and analyse AV operational data to support LTA’s regulatory and safety assurance work. But the role is broader than any single product: wherever software can move AV deployment forward, that is where we will build.

As a software engineer, you will

• Design and build production-quality digital products end to end: You will be expected to understand and take ownership of problem statements, before designing and architecting systems on cloud infrastructure — owning features from conception through deployment and ongoing maintenance.
• Build the suite of safety-assurance products LTA needs to regulate AVs reliably: analytics, dashboards and visualisations; implement enforcement and performance tracking, event management and data-anomaly alerts.
• Identify and address pain points bottlenecking deployment velocity: Work in a tight-knit and cross-functional CAM team, with a clear north-star of driving safe AV deployments at scale — which includes non-passenger vehicles and AVs on public paths (Autonomous Mobile Robots). Talk to users and industry, identify gaps and propose products that move AV deployments forward.
• Evolve our products to the next bound: Our product portfolio spans several digital products, including the AV Monitoring System that monitors every AV on Singapore’s public roads. We are building for scale so that systems can handle a growing number of AVs and developers amidst evolving needs; strengthening data pipelines and system observability for high-volume telemetry, and potentially integrating with other LTA enterprise platforms for operations and incident management.
• Keep what we ship healthy: monitor and support production systems that AV operations and regulation depend on, including helping respond to incidents when they arise.

Apply AI, ML and Data Analytics where it adds value

AI is increasingly central to how we build and what our products do. You can expect to apply it in areas such as:

• Engineering productivity: Safe use of AI tools, including coding assistants and multi-agent workflows, will be expected.
• Anomaly and risk detection: Automatically surface unsafe patterns found from AV operational telemetry and video data, so issues are caught earlier before scale.
• Operational intelligence: Address the pain points faced by operations and regulatory colleagues as deployments scale, through natural-language querying and automated summaries of performance and trends.
• Deployment and planning: Implement tools and optimisation algorithms to inform demand/supply estimation and deployment feasibility.

Because safety assurance is new ground, you will also

• Help shape what we build, not just how — identify gaps and propose products that strengthen AV safety and drive AV deployments.
• Work with policy, operations and regulatory colleagues to turn requirements into working software, and explain technical trade-offs to non-technical audiences.
• Know when to build versus when to adopt open-source or commercial solutions, so effort goes into delivering real value rather than re-solving solved problems.

If you join as a more senior hire, you will also

• Lead technical discussions, influence architectural decisions, and own technical direction across products.
• Establish testing, CI/CD and code-quality practices, and balance pragmatic delivery with long-term technical sustainability.
• Set engineering best practices, mentor other engineers and support recruitment.

If you want your code to shape how a new technology is adopted safely while driving deployment needs at scale, we want to hear from you.

[What we are looking for]

● Knowledge preferably in Computer Science, Software Engineering, or a related field.

●We’re generally language-agnostic and will use the most appropriate tool to solve the problem — core competency in at least one language and the ability to learn matter most. We look for someone who:

• Can build software end to end, and is strong across the stack — demonstrated through prior work, shipped products or personal projects; what you’ve built matters more than specific degrees. You should be comfortable designing and implementing digital products with maintainable data models.
• Thinks clearly about systems — data pipelines, APIs, data integrity and authentication, and designing for scale and reliability — making technical decisions that balance performance, maintainability and real-world needs.
• Listens and communicates well — able to listen and distil issues faced by stakeholders into key problem and/or opportunity statements to devise effective solutions, while being able to clearly explain and obtain buy-in from other engineers and key stakeholders.
• Takes initiative, has pride in their craft, and cares about the public good — writes tests, cares about code quality, maintainability and correctness. Self-directed and curious in picking up new knowledge, and invested in team success beyond individual contributions. Motivated by the mission of driving safe AV deployments at scale.

Useful, but not essential

• Experience with data-intensive systems, dashboards and data visualisation, or cloud infrastructure.
• UI/UX sensibility — experience designing usable interfaces, or working closely with designers to craft intuitive user experiences.
• Familiarity with our stack — we commonly use JavaScript/TypeScript with some Python, React, cloud services and open-source tooling, on relational databases (SQLite and Postgres). Additional familiarity in working with geospatial data and relevant libraries will be a plus.
• Familiarity with infrastructure-as-code (e.g. Terraform), CI/CD pipelines, and Agile delivery.
• Interest in autonomous vehicles, transport planning, generative AI, or safety-critical systems.