About the Team:

The Robotics Technology team is a core part of Grab's long-term vision to build urban embodied AI. Our engineers take full ownership of the product lifecycle: designing and manufacturing hardware in-house, developing control and machine-learning systems, and rigorously testing in real-world conditions and production fleet operations. This is a fast-moving, multidisciplinary environment where software, hardware and data science experts collaborate closely to solve practical challenges at scale. We are executing an ambitious growth plan to expand our robotics fleet across cities over the coming years, and we are focused on delivering highly productive, safe and efficient robot delivery services that help address current delivery labor shortages.

Based in Singapore and China, our team offers opportunities to work on cutting-edge autonomy, deploy solutions in complex urban environments, and directly influence the future of last-mile logistics. If you're excited by tangible impact, large-scale systems and cross-functional engineering, you'll find meaningful challenges and rapid career growth here.

Get to know the Role:

We are looking for a DevOps Engineer to own the engineering environments our robotics team builds on — cloud, developer workstations, and the robots themselves. Our software runs on ARM64 computers on a moving vehicle, is developed and run on Ubuntu, macOS and Windows, and is built and operated from two engineering sites with different network and cloud constraints. Your job is to make those environments consistent, reproducible and fast, so that an engineer at either site gets the same toolchain, the same build and the same behaviour on the robot. This is a broad, high-leverage role with a large surface area and a lot of latitude: you will set the standards, build the automation behind them, and take real ownership of a platform that is growing quickly alongside the fleet.

The day-to-day activities

• Own and evolve developer environment tooling across Ubuntu, macOS and Windows — reproducible, declarative and version-controlled setups rather than wiki instructions.
• Build and maintain CI/CD pipelines for cloud services, backend systems and cross-compiled embedded/robot software, including ARM64 targets.
• Own container image and artifact strategy: registries, base images, caching, provenance and promotion between environments.
• Manage the on-robot software environment: OS images, system packages, dependency pinning, and safe rollout and rollback of host-level changes.
• Build and operate cloud environments and Infrastructure as Code across regions, including networking, identity and access management.
• Standardize and unify toolchains and environments across our engineering sites, while respecting the constraints that genuinely differ between regions.
• Evaluate, specify and support developer and compute hardware — workstations, GPUs, test rigs and onboard compute — and own the lifecycle around it.
• Automate what is currently manual: provisioning, onboarding, credential rotation, environment refreshes and routine operational tasks.
• Improve build and test speed, and treat engineer wait time as a first-class metric.
• Write and maintain runbooks and internal documentation, and coach engineers so that platform knowledge is shared rather than concentrated.

Technical must-haves

• **Deep