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Salary: USD 250,000 - 300,000 / annual
Crusoe is a vertically integrated AI infrastructure company building the complete stack from energy to tokens to power large-scale AI workloads. The company is solving the power bottleneck in AI compute through an energy-first approach.
You will set the technical direction for Crusoe's Linux kernel team, owning the roadmap and architecting critical development projects. This role balances high-level architectural design with hands-on kernel coding, requiring you to tackle complex kernel problems while mentoring and growing the engineers around you.
Key responsibilities include:
- Virtualization Architecture: Design and implement advanced virtualization technologies for GPU-accelerated AI and HPC workloads, optimizing for low latency and high scalability across hypervisors and device emulation.
- Linux Kernel & Driver Development: Develop and maintain upstream-first kernel code and device drivers, optimizing memory management, scheduling, and I/O subsystems to support hardware accelerators and high-throughput compute.
- Debugging & Security: Perform deep-dive root-cause analysis across OS and hardware layers, lead triage and backporting for kernel CVEs, and build automated tooling for vulnerability analysis.
- Leadership: Lead and grow a high-performing systems team, driving engineering excellence through technical mentorship, comprehensive code reviews, and cross-functional alignment with product and hardware teams.
Required qualifications: 10+ years in systems software engineering with at least 3 years in a technical leadership role managing low-level systems or infrastructure teams. Expert-level knowledge of Linux kernel internals (memory management, scheduler, I/O) and virtualization technologies (KVM, Xen, QEMU). Strong C programming skills and fluency with kernel development workflow, patch submission, and security vulnerability debugging. Proficiency in modern systems programming (Go, Rust, Python) and familiarity with CI/CD and deployment automation.
Bonus: Experience with accelerators (GPUs, TPUs), CUDA/ROCm, high-performance networking (InfiniBand, RoCE), and HPC workload virtualization tuning.
