Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

About This Role

As a Principal Software Engineer for Infrastructure, you will partner with teams across the company to help shape the technical direction of the compute, storage, and networking platforms that power Crusoe’s AI-first cloud. This is a high-leverage leadership role that spans the full infrastructure stack: you will work alongside engineers and stakeholders on the systems that help massive GPU clusters run AI and HPC workloads at extreme throughput, low latency, and high reliability. Your work spans the Linux kernel, hypervisors and virtualization, distributed storage, network fabrics, and the control planes that tie them together.

You will be a trusted technical partner across the infrastructure stack, helping guide architecture decisions and mentoring engineers to raise our collective technical bar. You will look at the whole system alongside the teams who own each layer: how a storage tier, a scheduler, and a network fabric interact under a multi-node training job, and where the real bottleneck sits. You will collaborate closely with Product, Hardware, and Infrastructure teams to build a reliable, scalable platform together that aligns with Crusoe’s mission to innovate sustainably. This is a full-time position.

What You’ll Be Working On

Infrastructure Strategy: Partner with engineering, product, and leadership to help shape the long-term direction for compute, storage, and networking, and to turn that direction into practical plans and milestones.

Architecture & Design: Collaborate with teams on architecture reviews, design documents, and code reviews for critical infrastructure components and services across all three domains.

Compute & Virtualization: Work with compute teams on the virtualization and orchestration layers that deliver bare-metal-class performance to GPU workloads, including hypervisor tuning, SR-IOV, vDPA, virtio, device passthrough, and NUMA- and topology-aware scheduling.

Storage Systems: Work with storage teams on high-throughput, low-latency storage for training and inference pipelines, including distributed block, file, and object storage, NVMe and NVMe-oF, RDMA-based data paths, and checkpointing and data-loading performance.

Networking & Fabric: Partner with networking teams on architectures for GPU-to-GPU fabrics, high-speed Ethernet, and specialized AI clusters, using technologies such as XDP, eBPF, DPDK, OVS/OVN, BGP, EVPN, and VXLAN.

Kernel & Driver Work: Contribute to Linux kernel modules and high-performance drivers across the network, storage, and device stack.

Hardware Integration: Work with Hardware teams on accelerators and offload devices, including GPUs, SmartNICs, DPUs, IPUs, and NVMe, from qualification through bring-up of new platforms.

Cross-Stack Performance & Reliability: Team up with on-call, SRE, and domain engineers to troubleshoot complex production issues that cross compute, storage, and network boundaries, and to improve performance, observability, capacity planning, and failure-domain design.