Automate the bare-metal lifecycle: hardware discovery and inventory, server bring-up, imaging, firmware and driver configuration, out-of-band management, health checks, reprovisioning, and recovery.
Build CI services that allocate the right hardware, provision repeatable test environments, record hardware and software configurations, collect diagnostics, and restore systems to a known state. Shorten the path from a hardware or software change to actionable validation results.
Keep engineering services dependable while supporting evolving preproduction hardware and software. Define service-level objectives, isolate failures, improve observability, and turn incidents and recurring test-infrastructure failures into engineering fixes.
Measure and improve hardware onboarding time, provisioning speed, CI queue time, productive fleet utilization, recovery time, and cost efficiency as capacity expands.
Set engineering standards for design and code reviews, automated testing, secure development, release quality, and safe changes to production systems.
Hire, coach, and retain engineers and engineering managers. Establish clear ownership, develop technical leaders, and build teams that deliver consistently over multiple release cycles.
Partner with hardware, firmware, drivers, networking, storage, security, and validation teams to onboard platforms and diagnose failures across system boundaries. Translate engineering users’ needs into clear priorities and technical decisions.
Work with datacenter operations and facilities teams to bring additional capacity online. Connect rack power, cooling, physical topology, and hardware-health telemetry to provisioning, placement, serviceability, and operational readiness.
What we need to see
15+ overall years of experience in software engineering, distributed systems, or cloud infrastructure, including 7+ years leading engineering teams and experience managing engineering managers.
Direct engineering ownership of the underlying services of a public or private compute cloud, such as AWS EC2, Google Compute Engine, Azure Compute, OCI Compute, or a comparable infrastructure-as-a-service platform.
Strong technical depth in distributed systems, Linux, virtualization, containers, and the networking and storage services that support large compute fleets.
Experience building software and automation for bare-metal infrastructure, including server provisioning, hardware inventory, firmware or operating-system lifecycle management, and recovery across heterogeneous systems.
Experience running production infrastructure with demanding availability requirements, including failure isolation, incident response, observability, and reliable deployment and recovery mechanisms.
The ability to guide architecture, evaluate implementation choices, and debug complex interactions among hardware, firmware, drivers, operating systems, and distributed services with senior engineers.
A record of sustained ownership as platforms evolve, with measurable improvements in reliability, scalability, or engineering delivery. Strong communication, collaboration, and people-development skills.
A degree in computer science, computer engineering, or a related discipline, or equivalent experience.
Ways to stand out from the crowd
Experience building or operating OpenStack infrastructure, particularly Nova, Neutron, Cinder, or Ironic, or contributing to related open-source projects.
Engineering leadership spanning compute control planes and site reliability, including multi-tenant isolation, scheduling, placement, and capacity allocation.
Experience with GPU clusters, rack-scale computing, NVLink, InfiniBand or high-speed Ethernet, and AI or high-performance computing workloads.
Experience supporting preproduction hardware, new product introduction, or hardware-in-the-loop CI, including repeatable validation environments and systematic regression isolation.
Familiarity with liquid-cooled, high-density datacenters and how power, thermal constraints, cooling, and component health affect fleet availability and scheduling and delivery of compute platforms across multiple regions, datacenters, or hybrid-cloud environments, including fleet upgrades and workload migration with minimal service disruption.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 320,000 USD – 488,750 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
