Staff Product Manager (Bare Metal)

Join Crusoe, a leading company in the AI-native technology space. As the Staff Product Manager for Bare Metal, you will own the strategy and outcomes for our new bare metal offering, providing direct GPU and CPU access to power demanding training and inference workloads. This role requires technical depth across hardware, firmware, and operating system layers, as well as process rigor to design the product's operational behavior. You will drive the vision for bare metal compute, define the end-to-end customer experience, ensure alignment between hardware and software layers, lead cross-functional initiatives, synthesize customer and market feedback, and represent the bare metal strategy to partners and internal executives.

• Drive the vision for bare metal compute, encompassing GPU/CPU offerings, rapid provisioning systems, and full lifecycle management.
• Define the end-to-end customer experience when something goes wrong — the ticketing workflow, escalation paths, and process behind it — in close partnership with Infrastructure Operations and Customer Support.
• Lead initiatives across engineering and infra-ops to deliver provisioning, enhanced observability, and customer self-service capabilities.

• Process Orientation: A demonstrated ability to design and formalize operational processes (support workflows, ticketing, incident handling) for a technical product
• Communication Mastery: The ability to articulate deep technical complexity to executive audiences and translate business goals into clear product direction
• Infrastructure Leadership: 10+ years of experience in cloud and computing technology, including 4+ years in product management focused on infrastructure or platform products, with a track record of leading complex, cross-functional initiatives through ambiguity
• Strategic Decision Making: Proven ability to navigate ambiguous, ill-defined problem spaces and drive long-term vision while balancing technical constraints and business outcomes
• Deep Compute & Operational Expertise: Comprehensive knowledge of server hardware, bare metal provisioning, distributed systems, networking, and large-scale fleet operations
• Hardware Depth: Direct experience at the hardware and firmware level, you don't need to be an engineer, but you need to have worked at that layer
• AI/ML Domain Knowledge: An understanding of GPU-based AI workloads and their specific demands on compute and network infrastructure
• Technical Tooling: Familiarity with IPMI/BMC protocols, infrastructure automation tools, or bare metal provisioning frameworks
• Hyperscale/Cloud Operations: Experience with large-scale GPU/CPU AI infrastructure platforms or clouds