Crusoe Staff Product Manager, AI Infrastructure (Storage) at Crusoe owning long-term architecture and technology strategy for storage stack powering AI workloads. Partners with engineering and architecture teams to scale storage infrastructure.
Responsibilities
Crusoe is building the infrastructure layer that powers the most demanding AI workloads on the planet. Our storage stack is what keeps tens of thousands of GPUs fed with data, whether that means block volumes for fast bootups, a shared file system for a training cluster, or the object storage tier a physical AI customer depends on. As a Principal Product Manager on our AI Infrastructure team, you will own the long-term architecture and technology strategy for Crusoe's storage foundation: how we build our storage stack at scale, from hardware and vendor selection to fleet-wide deployment architecture.
This is a foundations role. You will work as a peer to our most senior infrastructure engineers and architects, and make the long-term architecture, vendor, and technology decisions that determine whether our storage platform can scale for years, not just for the next customer request. You will partner closely with Infrastructure Engineering, Cloud Software Engineering, and Architecture to translate future workload, fleet, and customer requirements into infrastructure requirements, and manage the vendor relationships that keep our storage stack world-class for AI at scale.
What You'll Be Working On
Long-term vision: Define the 2-4 year vision and roadmap for Crusoe's storage foundation, across block, file, object, local NVMe, and archival tiers.
Architecture and hierarchy: Own the long-term storage architecture and hierarchy
Vendor management and technology strategy: Own Crusoe's long-term vendor management strategy for the storage stack, and shapes our cost structure, capital allocation, and competitive position.
Platform targets: Set the performance and durability targets the platform must hit, including storage cost per usable TB and capacity efficiency.
Scale for AI: Own the future architecture required to support significantly larger AI clusters and fleet scale.
Structural investment: Identify structural limitations in the current architecture and prioritize the long-term investments that resolve them.
Engineering partnership: Partner with Infrastructure Engineering and Architecture on major technical tradeoffs, and define the product requirements and business rationale behind foundational investments.
Industry scouting: Actively scout the industry for emerging storage technologies and vendors, and represent storage foundations in leadership reviews.
What You'll Bring to the Team
Qualification
Experience with AI/ML infrastructure
Preferred
Experience with AI/ML infrastructure, including training and inference workloads in the cloud.
Direct experience with high-performance storage networking, such as RDMA or GPUDirect Storage.
Experience with a major cloud provider (AWS, Azure, GCP) and their storage services, or a deep understanding of cloud-native storage principles at hyperscale.
Experience managing or mentoring other product managers
