Staff Product Manager, AI Compute Platform

Crusoe; San Francisco (CA); On-site; USD 208,725 - 253,000; Full time

Benefits offered by this job

Competitive compensation

RSUs

Paid time off

Health, dental & vision insurance

Parental leave

401(k) Retirement plan

Job summary

Crusoe is building the future of AI infrastructure from the ground up in San Francisco. The Product Manager, Compute leads Crusoe Cloud's core compute offerings—from GPU/CPU infrastructure to bare metal and virtualized compute—powering AI training and inference workloads.

You will shape hardware and software capabilities, optimize scheduling and performance, and partner with engineering, operations, finance, and GTM teams to deliver scalable, cost-efficient compute platforms for AI-native and

Qualifications

• Proven experience delivering infrastructure or platform products in cloud/HPC/AI environments.
• Deep understanding of virtualization, containerization, distributed systems, and large-scale cluster operations.
• Familiarity with AI infrastructure workloads and GPU-based training/inference.

Responsibilities

• Define and execute product strategy for Crusoe Cloud compute services (GPU/CPU, bare metal, virtualized).
• Translate AI workload requirements into product capabilities for performance, scheduling, isolation, and reliability.
• Drive roadmap decisions across hardware platforms and cluster topologies.
• Collaborate with engineering, operations, finance, and GTM to deliver scalable compute platforms.

Skills

Infrastructure product management

Compute infrastructure

GPU/CPU knowledge

Scheduling and performance

Strong analytical skills

Cross-functional collaboration

Tools

Kubernetes

Slurm

Job description

Crusoe is building the future of AI infrastructure from the ground up in San Francisco. The Product Manager, Compute leads Crusoe Cloud's core compute offerings—from GPU/CPU infrastructure to bare metal and virtualized compute—powering AI training and inference workloads.

You will shape hardware and software capabilities, optimize scheduling and performance, and partner with engineering, operations, finance, and GTM teams to deliver scalable, cost-efficient compute platforms for AI-native and