About the role
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: At Crusoe Energy Systems, we are building the most sustainable, AI-first cloud infrastructure, and our Compute-focused Production Engineers are the backbone of that mission. This role is centered on supporting virtualization, hypervisor, and kernel-level performance for Crusoe’s compute infrastructure. You’ll play a vital role in deploying and optimizing bare-metal and virtualized compute platforms, ensuring performance, security, and scale for modern AI and HPC workloads. What You'll Be Working On: In this role, you will develop automation and observability tools to monitor Crusoe’s compute infrastructure, spanning from the kernel to orchestration layers. You will support and scale the company’s virtualization stack, including technologies such as KVM, QEMU, and other hypervisors. Collaborating with Linux kernel and hardware teams, you’ll help identify and resolve performance bottlenecks, driver issues, and optimize hardware offloads. A key focus will be on optimizing performance for AI and HPC workloads across CPU, GPU, and DPU/NIC resources. You will participate in root cause analysis for kernel crashes, hardware-software integration problems, and performance regressions, while also integrating hypervisor-level enhancements to improve guest VM reliability and workload isolation.
