Senior Staff Infrastructure Engineer - Virtualization
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 23h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 123d ago
The date the source published, not the day we noticed it (2026-05-14). Last seen at its source just now.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
No source stated where this role may be worked. This is read from the ad's own words.
What the ad says
…authorization to work in United States, as required by law…
Pay not stated
Similar roles pay $195.1k–254.5k/yr
Middle 50% of 550 listings that do state pay — Engineering · Lead · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
ashby employer's own board first seen 11d ago · last seen just now
- location not stated
The listing
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.
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.
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
Who You Are
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
What We Offer
Stock Options
100% paid Medical, Dental, and Vision insurance for Employees
Company Health Savings Account Contributions
100% paid Short Term and Long Term Disability Insurance for Employees
Life and Voluntary Supplemental Insurance Options
Other Insurance Options, such as Pet & Legal Insurance
Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support
Flexible Spending Account
401(k)
Employee Assistance Program
Flexible PTO
Paid Holidays
Parental Leave
Other In-Office Perks
Equal Employment Opportunity
TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.
Reasonable Accommodations
TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.
Employment Eligibility
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.