About the Role

At Crusoe, the Capacity Planning & Efficiency team operates at the critical intersection of all Crusoe products, services, and underlying physical infrastructure. This role focuses specifically on the end-to-end forecasting, optimization, and lifecycle management of Compute (CPUs) and Storage architectures (including File, Object, and Block storage) across Crusoe Cloud's infrastructure topology. You will be part of a team optimizing global and regional capacity plans at various altitudes to balance service levels, performance tiers, capital constraints, and financial targets.

This role is uniquely positioned to maximize server and storage fleet utilization with company-wide impact, directly supporting Crusoe's mission to align the future of computing with environmental sustainability. The ideal candidate will collaborate deeply across cloud engineering, product management, and supply chain teams to scale one of the world's most innovative AI-first clouds.

What You'll Be Working On

• End-to-End Capacity Modeling: Own and manage the multi-quarter capacity plans and allocation models for core infrastructure resources across Compute (CPUs) and multi-tiered Storage platforms (File, Object, and Block arrays).
• Demand Forecasting & Signal Analysis: Analyze demand signals, historical workload profiles, customer usage shifts, and product roadmaps to build highly precise resource consumption forecasts to guide strategic hardware placement strategies.
• Cross-Functional Collaboration: Partner closely with Sales, Storage Engineering, Server Hardware Engineering, SRE, Product, Finance, and Supply Chain to translate high-level product forecasts into physically deployed hardware allocations while navigating global procurement lead times.
• Efficiency & Financial Optimization: Interface directly with Finance and Product to tightly balance structural cost efficiency, infrastructure unit economics, depreciation schedules, and hardware utilization targets against technical availability cushions.
• Automation Requirements: Define operational metrics, establish planning baseline standards, and partner with Software Engineering teams to architect, automate, and implement automated capacity workflows and real-time visualization dashboards.
• Data Mining & Validation: Perform complex data mining and verification across raw hardware usage metrics, asset management databases, and financial billing pipelines to guarantee maximum structural accuracy in capital efficiency models.

What You'll Bring to the Team

• Proven Capacity Domain Expertise: 3+ years of direct experience in Infrastructure Capacity Planning, Infrastructure Systems Engineering, or Technical Product Management with heavy exposure to compute and storage.
• Deep Hardware & Architecture Familiarity: Demonstrated foundational technical knowledge of enterprise server configurations, CPU sizing/benchmarking, and storage across File, Object, and Block storage infrastructures.
• Hyper-Growth Experience: Experience working inside high-growth, fast-paced public cloud environments or massively distributed systems topologies.
• Excellent Communication: Strong structured narrative delivery, documentation, and cross-functional negotiation skills to successfully bridge alignment across engineering technicalities and business/financial constraints.
• Education: Bachelor's or Master's degree in Computer Engineering, Computer Science, Operations Research, Mathematics, Data Science, or an equivalent technical/quantitative field.

Bonus Points

• Experience building or defining foundational product requirements for custom in-house software automation tools used for machine-level monitoring, resource provisioning, or automated capacity modeling.
• Willingness and capacity to scale scope into specialized GPU clusters and cutting-edge accelerated AI computing fabrics as the underlying infrastructure footprint expands.

Compensation Range

Compensation will be paid in the range of up to $195,000 - $235,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.