What You’ll Work On
- Define and execute the product strategy for Crusoe Cloud compute services, including GPU and CPU infrastructure, bare metal offerings, and virtualized compute environments supporting AI training and inference workloads
- Translate emerging AI workload requirements into product capabilities across performance, scheduling, isolation, utilization, and reliability
- Drive roadmap decisions across hardware platforms, including new GPU generations, server architectures, and cluster topologies, ensuring alignment between infrastructure investments and customer demand
- Partner with engineering and infrastructure teams to deliver fleet-level capabilities such as provisioning, lifecycle management, observability, and performance optimization across large-scale compute environments
- Collaborate with networking and storage product teams to ensure integrated infrastructure performance for distributed AI workloads
- Define pricing and packaging models that balance utilization, customer flexibility, and long-term infrastructure economics
- Work closely with sales, customer success, and solutions engineering to incorporate customer feedback into roadmap prioritization and product iteration
- Lead cross-functional execution from concept through launch, coordinating efforts across Product, Engineering, Operations, Finance, and GTM teams
- Develop executive-level narratives and decision materials that inform capital allocation, capacity planning, and product direction
- Represent Crusoe’s compute strategy internally and externally, supporting technical discussions with customers and partners as needed
What You’ll Bring
- Strong product management experience delivering infrastructure or platform products, ideally within cloud infrastructure, HPC, or AI/ML environments
- Deep understanding of compute infrastructure concepts including virtualization, containerization, distributed systems, and large-scale cluster operations
- Familiarity with GPU-based workloads and AI infrastructure, including training and inference characteristics, scheduling challenges, and performance considerations
- Experience working across hardware and software boundaries, translating infrastructure capabilities into customer-facing products
- Ability to balance technical tradeoffs, customer requirements, and infrastructure economics when making product decisions
- Strong analytical skills with the ability to interpret utilization, performance, and financial metrics to guide roadmap prioritization
- Experience collaborating across engineering, operations, finance, and GTM teams to deliver complex infrastructure products
- Strong communication skills with the ability to articulate technical concepts and connect them to customer and business outcomes
Bonus Points
- Experience working with large-scale GPU fleets or AI infrastructure platforms
- Familiarity with Kubernetes, Slurm, or other workload orchestration systems used for AI and HPC workloads
- Experience building products for AI-native customers or operating AI workloads directly
- Background in infrastructure economics, capacity planning, or capital-intensive product environments
Compensation Range
Compensation will be paid in the range of $208,725 - $253,000 + Bonus. Restricted Stock Units are included in all offers.