Crusoe

Principal Systems Architect role focused on designing and leading the development of next-generation AI infrastructure, specifically the I/O path for massive-scale AI workloads. This involves unifying Bare-Metal-as-a-Service, Intelligent IaaS, and Elastic CaaS, optimizing hardware-software co-design, and leading R&D teams to ship production-grade kernel and orchestration code. The role requires deep expertise in Linux kernel, virtualization, high-performance networking, and experience from hyperscale environments.

Crusoe is an AI infrastructure company building and operating compute platforms for AI workloads. This Systems Engineer II role focuses on designing, developing, and optimizing the compute platform, specifically for virtualized AI platforms. Responsibilities include managing virtualization stacks across thousands of servers, integrating with AI hardware, optimizing performance for AI/ML workloads, and troubleshooting complex system issues. The role requires strong Linux systems knowledge, hardware integration experience, distributed systems design, and software development skills.

Staff Product Manager for Orchestration at Crusoe, an AI infrastructure company. The role focuses on defining and owning the foundational orchestration services for large-scale AI workloads (training, fine-tuning, inference) on their AI cloud. This involves managing Kubernetes offerings and underlying infrastructure, balancing reliability, scale, and platform implications, and driving product lifecycle end-to-end. Requires deep technical fluency in orchestration systems and cloud infrastructure, with a strong product management background.

This role focuses on developing software for managing a fleet of GPU servers and data centers, with an emphasis on diagnostics, observability, automation, and repair tooling for high-performance GPU compute clusters. It involves developing AI agents for hardware diagnosis and remediation, and tooling for critical environment management and post-repair validation.

Senior Staff Cloud Support Engineer role focused on supporting and improving AI/ML infrastructure, including GPU clusters, distributed training, and inference. The role involves technical leadership, incident response, reliability architecture, and customer-facing authority, with a strong emphasis on Kubernetes, networking (Infiniband, RDMA, RoCE), and Linux systems.