Asset Manager, Supply Chain

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.

Crusoe is seeking a highly organized and strategic Asset Manager to oversee and optimize the lifecycle of hardware and software assets across our Crusoe Cloud Data Center deployments. This role is critical for ensuring accurate inventory tracking, proactive license and support management, and deep visibility into our high-value compute, networking, and storage environments. We are looking for a meticulous operator who brings a strong background in IT Asset Management (ITAM), contract tracking, and infrastructure hardware to the team. This is a full-time position with flexibility to be based in San Francisco (CA), Sunnyvale (CA), Seattle (WA), or Denver (CO).

• Professional certification such as CHAMP, CSAM, CITAM, or ITIL.

• Experience managing assets in a hyperscale, AI-focused cloud, or high-performance computing (HPC) environment.

• Experience with Excel/Spreadsheet Data Modeling and Dashboarding.

• Proficiency in scripting or automation (e.g., Python, SQL) for reconciling large asset datasets.