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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Infrastructure Engineer - Virtualization - **Company:** TensorWave Inc. - **Location:** Las Vegas, NV, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Proxmox, Artificial Intelligence, Systems Engineering, Cloud Computing, Computer Networks, Data Centers, Linux, Distributed Data Store, Distributed Systems, Memory Management, Hardware Virtualization, Hypervisor, Kernel-Based Virtual Machine, Network Layer, Networking Basics, PCI Express, Performance Tuning, Quick EMUlator (QEMU), Remote Direct Memory Access, Ansible, Systems Integration, Virtual Local Area Networks, Virtual Machines, Virtualization Technology, Weka, Ceph (Software), Graphics Processing Unit (GPU), Computer Network Operations, Offline Storage, Non-Uniform Memory Access, Kubernetes, Infrastructure Automation Frameworks, Bare Metal, Terraform - **Published:** November 5, 2026 - **Apply:** https://www.careerbuilder.com/job-details/staff-infrastructure-engineer-virtualization-las-vegas-nv--73bcd6eb-6c6d-44b2-9575-c5388f72fc2e ## About the Role Virtualization, Artificial Intelligence (AI), Network Operations Center, GPU (Graphics Processing Unit), Power Generation, Hypervisors, Linux Operating System, K Virtual Machine (KVM), Hardware Virtualization, Problem Solving Skills, * 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 ## Description 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. What Youll 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, All offers of employment are contingent upon verification of identity and authorization to work in United States, as required by law. Background Checks Where permitted by law, employment may be contingent upon the successful completion of a job-related background check. Data Privacy Notice By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.