Staff Infrastructure Engineer - Virtualization

About The Role

We are building large-scale, high-performance infrastructure to power next-generation AI workloads. Our platform operates across multiple data centers and supports GPU-intensive environments with demanding requirements around performance, isolation, and scalability. We are looking for a Staff Infrastructure Engineer to lead the design and evolution of our virtualization platform.

What You’ll Do

• Design and implement a scalable virtualization platform capable of supporting high-density compute and GPU workloads
• Lead the evolution from existing platforms (e.g., Proxmox) toward KVM/QEMU-based architectures
• Define standards for VM lifecycle management (provisioning, scheduling, migration), performance isolation and resource allocation, failure domains and resilience strategies
• Optimize virtualization for high-performance workloads, including NUMA alignment, CPU pinning and scheduling, PCIe topology awareness, GPU passthrough and device assignment
• Partner closely with networking and storage teams to integrate high-throughput, networking (e.g., SR-IOV, RDMA), distributed and local storage systems
• Build and improve automation for hypervisor deployment and configuration, image pipelines, cluster scaling and lifecycle management
• Troubleshoot deep system-level performance issues across compute, memory, storage, and network layers
• Contribute to long-term platform architecture and infrastructure strategy

Required Qualifications

• 7+ years of experience in infrastructure, systems engineering, or platform engineering
• Deep experience with Linux-based virtualization, including: KVM/QEMU, libvirt or similar tooling
• Strong understanding of: CPU scheduling and NUMA architectures, memory management and performance tuning, storage I/O paths and performance characteristics
• Experience designing and operating virtualization platforms at scale (hundreds+ hosts)
• Solid networking fundamentals, including: Linux networking (bridges, bonding, VLANs), high-performance networking concepts
• Experience with infrastructure automation (e.g., Ansible, Terraform, or similar)
• Strong troubleshooting skills across distributed systems

Preferred Qualifications

• Experience in cloud or CSP environments (public or private)
• Familiarity with: GPU workloads and passthrough (VFIO), SR-IOV and advanced NIC features
• Experience integrating virtualization with: Kubernetes platforms, bare metal provisioning systems (e.g., MAAS)
• Exposure to distributed storage systems (e.g., Ceph, Weka, or similar)
• Experience working in high-performance or low-latency environments