Staff Software Engineer (Cloud Infrastructure)

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

We are seeking a highly skilled and motivated GPU Fleet Operations Engineer to join Crusoe’s Fleet Operations team. This role is focused on the advanced diagnosis, maintenance, and repair of high-performance GPU compute clusters, ensuring maximum uptime, reliability, and performance across our fleet.

The ideal candidate will be hands-on with GPU rack-level troubleshooting and work closely with data center operations, engineering, and vendors to support cutting-edge infrastructure featuring the latest NVIDIA and AMD GPUs. This position plays a critical role in maintaining the health and scalability of Crusoe’s rapidly growing GPU fleet.

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  Automate deep-level diagnosis and troubleshooting of hardware faults within GPU racks and high-density compute systems.

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  Develop software to troubleshoot and support GPU platforms including NVIDIA A100, H200, GB200, B200, B300 and AMD 350X / 355X.

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  Execute component-level diagnosis and remediation for failed or degraded hardware.

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  Partner with data center operations to manage and perform field-replaceable unit (FRU) repairs for GPUs, power supplies, cooling systems, interconnects, and networking hardware.

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  Conduct post-repair validation, burn-in testing, torch testing, and NVIDIA NCCL testing to ensure system stability and performance.

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  Implement and execute preventative maintenance procedures to improve fleet reliability and extend hardware lifespan.

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  Perform firmware and BIOS upgrades across the GPU fleet.

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  Maintain detailed documentation of maintenance activities, failures, and resolutions in ticketing and asset management systems.

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  Develop and update standard operating procedures (SOPs) for troubleshooting, repair, and validation workflows.

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  Collaborate with engineering, software, and data center operations teams to identify root causes of systemic failures and implement preventative solutions.

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  Participate in a rotating infrastructure on-call schedule (about one week every 4–6 weeks) with daytime coverage and handoff to the Europe team.
  

• Ability to code in Golang

• Proven experience diagnosing and repairing high-density, rack-mounted compute hardware in production environments.

• Deep understanding of GPU architectures and hands-on experience with GPU-based systems.

• Experience supporting NVIDIA A100, H200, GB200, B200 and AMD 350X / 355X series platforms.

• Familiarity with high-speed interconnects such as InfiniBand, NVLink, and RDMA over Converged Ethernet (RoCE).

• Strong Linux experience (Ubuntu, Rocky Linux, CentOS) using the command line for diagnostics and testing.

• Proficiency with GPU and system diagnostic tools such as NVIDIA DCGM and NVIDIA field diagnostic utilities.

• Experience working with enterprise server hardware, power delivery, and cooling systems.

• Strong analytical and problem-solving skills.

• Excellent communication and collaboration skills.

• Ability to work independently in a fast-paced data center or operations environment.

• Technical certification or Associate’s/Bachelor’s degree in Electrical Engineering, Computer Science, or a related field or demonstrated experience.

• Experience working directly with hardware vendors and escalations.

• Background in large-scale GPU fleet operations or hyperscale data center environments.