Staff, Cloud Infrastructure Engineer

Role overview

Staff, Cloud Infrastructure Engineer (Advanced Research Team within the Office of the CTO). You’ll focus on the foundational “compute” layer—how resources are provisioned, configured, and optimized at runtime across bare metal, VMs, containers, and major cloud providers.

What you’ll do

• Own and evolve how compute infrastructure is provisioned and operates across heterogeneous environments (bare metal, VMs, containers, cloud)
• Define and tune system-level behavior across CPU, memory, storage, and network, including scheduling and resource utilization
• Design repeatable and auditable provisioning/deployment workflows using infrastructure-as-code (e.g., Terraform, Pulumi, or similar)
• Shape runtime characteristics such as startup behavior, workload placement, and resource efficiency as systems scale
• Identify and resolve bottlenecks across I/O throughput, network behavior, and provisioning performance
• Use AI-assisted development tools to explore, implement, iterate, and refine infrastructure designs into production-ready systems

Who you’ll work with

• Collaborate with control plane engineering to establish a clear, stable foundation for higher-level services.

Requirements

• Systems/infrastructure experience, including OS behavior, runtime environments, or low-level interactions
• Experience operating Kubernetes (or similar), including scheduling behavior, node-level characteristics, and cluster lifecycle concerns
• Familiarity with containerization, virtualization, and infrastructure provisioning across cloud and on-premises
• Ability to design systems for multi-environment portability and consistency
• Understanding of distributed systems and how resource constraints impact performance and scalability
• Experience with observability, profiling, or system-level performance analysis
• Comfort working in a rapidly evolving environment where system direction is actively changing

Nice to have

• Exposure to query engines / analytical data platforms (e.g., Presto, Trino, Spark, DataFusion)
• Background in big data infrastructure or data pipelines