Staff Infrastructure Engineer - Virtualization
External
Tensorwave · Las Vegas, NVPrepare for this interview
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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. This role will own how we build, scale, and operate hypervisor infrastructure as we transition from traditional virtualization platforms toward a more flexible, CSP-aligned architecture based on KVM/QEMU and modern Linux primitives . This is a highly technical, hands-on role focused on solving complex systems problems at scale.
Responsibilities
- 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
Requirements
- 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
- 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
Benefits
Additional Information
About TensorWave Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.
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