Lead Software Engineer, Infrastructure at Grab

Get to Know 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 seeking an experienced and passionate Lead Software Engineer, Infrastructure (Lead Site Reliability Engineer) to join our robotics platform team in Singapore. You will work with a small, highly experienced engineering group building and maintaining the cloud and backend infrastructure that powers our robot fleet, simulation environments, data pipelines and ML model training/deployment. You will own the reliability, scalability and observability of systems used both in production robot operations and engineering/data science workflows. Initiative, strong problem‑solving skills and an operator-first mindset are critical — you'll proactively identify problems, build robust solutions, and help the broader team run and scale complex distributed systems. You will report to the Senior Principal Engineer. Work Type: 5-day onsite. The Critical Tasks You Will Perform • Design, build and operate scalable cloud infrastructure and IaC for fleet management, telemetry ingestion, data lakes, model training, and CI/CD for embedded and cloud services. • Implement and maintain observability (metrics, tracing, logging) and alerting for robot operations, simulation, and platform services. • Lead incident response, root cause analysis, postmortems and implement corrective engineering to prevent recurrence. • Automate operational tasks: deployments, rollbacks, canary releases, capacity scaling, backups and failover. • Collaborate with software, hardware, ML, and operations teams to define SLOs/SLIs and ensure systems meet availability and performance targets. • Build and scale data and model training pipelines (batch/streaming), and provide reliable compute/resource platforms for training and inference. • Harden systems for security, access control and compliance in production and test environments. • Mentor and grow SRE and platform engineers; drive platform best practices, runbooks and runbook automation. • Support and improve simulation and mapping infrastructure used by engineers and data scientists.