Staff Software Engineer, Core Infrastructure

Uber Uber · Consumer · Aarhus, Denmark · Engineering

Staff Software Engineer focused on building and scaling mission-critical backend infrastructure systems at Uber, including deployment engines, autoscalers, and hybrid cloud environments. The role emphasizes improving quality, security, modernization, and efficiency across the company's infrastructure.

What you'd actually do

  1. Design and implement backend infrastructure components to support Uber’s growing workloads, including deployment engines, autoscalers, and hybrid cloud environments.
  2. Lead cross-team projects focused on safe deployment and rollback automation across stateless, stateful, and batch workloads, improving resilience and developer efficiency.
  3. Improve infrastructure security and compliance, including encryption-at-rest, ransomware mitigation, and cloud security best practices.
  4. Contribute to and drive modernization efforts within the team and across related teams, including Kubernetes migration, unified workload platforms, and PaaS improvements.
  5. Optimize Uber’s infrastructure efficiency, focusing on ARM adoption, autoscaling enhancements, and cost-effective compute allocation.

Skills

Required

  • backend software development
  • distributed systems
  • infrastructure
  • cloud platforms
  • Go
  • Java
  • Kubernetes
  • high-scale systems

Nice to have

  • highly available cloud-native/kubernetes architectures
  • efficient cloud-native/kubernetes architectures
  • secure cloud-native/kubernetes architectures
  • safe deployment strategies
  • workload automation
  • resilience engineering
  • scaling autoscaling solutions
  • ARM adoption
  • hybrid cloud
  • GPU support for ML workloads
  • complex cross-team engineering projects
  • strategic relationships with stakeholders

What the JD emphasized

  • 8+ years of experience in backend software development with distributed systems, infrastructure, or cloud platforms.
  • Strong expertise in Go, Java, or similar backend languages, with a deep understanding of Kubernetes, cloud infrastructure, and high-scale systems.
  • Experience leading cross-team or team-wide projects focused on system modernization, performance optimizations, and deployment safety improvements.
  • Strong experience in scaling autoscaling solutions, ARM adoption, hybrid cloud, or GPU support for ML workloads.