Product Manager; Compute

Responsibilities

• The Product Manager, Compute is responsible for defining and delivering Crusoe Cloud’s core compute offerings, spanning GPU and CPU infrastructure, bare metal, virtualized compute, and orchestration layers that power AI training and inference workloads. This role owns the strategy and execution of compute capabilities that form the foundation of Crusoe’s IaaS and Managed AI services
• You will define how customers access and consume large-scale compute resources, translating evolving AI workload requirements into scalable, reliable, and economically efficient products. This includes shaping infrastructure capabilities across hardware platforms, fleet management, scheduling, performance optimization, and developer experience. The role operates at the intersection of infrastructure, economics, and product strategy, ensuring compute investments translate into customer value and business outcomes
• The Product Manager, Compute collaborates closely with engineering, infrastructure operations, networking, storage, finance, sales, and customer success teams to deliver compute platforms that meet the needs of AI-native companies and enterprise customers running demanding workloads at scale
• 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

• Health & wellbeing:
  Comprehensive health benefits designed to support your overall wellness
• Time away:
  Paid time off for vacations, family bonding, and unexpected needs
• 401(k) match:
  Build your financial future with our 401(k) matching program
• Mental wellness:
  Resources and support for your emotional wellbeing and navigating life’s challenges

• Strong communication skills with the ability to articulate technical concepts and connect them to customer and business outcomes
• Deep understanding of compute infrastructure concepts including virtualization, containerization, distributed systems, and large-scale cluster operations
• Strong product management experience delivering infrastructure or platform products, ideally within cloud infrastructure, HPC, or AI/ML environments
• Ability to balance technical tradeoffs, customer requirements, and infrastructure economics when making product decisions
• Experience working across hardware and software boundaries, translating infrastructure capabilities into customer-facing products
• Experience collaborating across engineering, operations, finance, and GTM teams to deliver complex infrastructure products
• Strong analytical skills with the ability to interpret utilization, performance, and financial metrics to guide roadmap prioritization
• Familiarity with GPU-based workloads and AI infrastructure, including training and inference characteristics, scheduling challenges, and performance considerations
• Background in infrastructure economics, capacity planning, or capital-intensive product environments
• Familiarity with Kubernetes, Slurm, or other workload orchestration systems used for AI and HPC workloads
• Experience working with large-scale GPU fleets or AI infrastructure platforms
• Experience building products for AI-native customers or operating AI workloads directly