Staff Software Engineer

Join Crusoe, a company on a mission to accelerate the abundance of energy and intelligence. As a Staff Software Engineer on the Cloud Availability Platform team, you will help build Conductor, a self-driving control plane designed to optimize AI compute energy efficiency. You will have true ownership over greenfield services and tackle rare infrastructure challenges. This is a full-time position for a problem-solving engineer who thrives in ambiguity and has a strong bias toward shipping.

If you are excited to build foundational infrastructure that turns tens of thousands of accelerators across sites into one cohesive, logical system, this role offers an unprecedented opportunity to do the most meaningful work of your career

Responsibilities

• Design, build, and operate greenfield distributed services, control planes, and closed-loop remediation systems that automatically manage AI workloads.
• Collaborate closely with cross-functional partners to align system design with physical infrastructure and ensure safety in autonomous operations.
• Own the development of core platform features such as unified observability pipelines, energy-aware compute scheduling, and self-qualifying hardware pipelines.
• Distributed Systems Foundations: Demonstrated mastery of state reconciliation, retries and idempotency, consistency tradeoffs, and autonomous automation on live infrastructure
• Observability Architecture: Prior experience designing scalable observability and telemetry pipelines that span compute, storage, and networking layers

Requirements

• Problem-Solving & Ownership: High comfort level working through ambiguous problem statements, proposing clear designs, and driving features from concept to production
• Educational Background: Bachelor's degree or equivalent practical experience in Computer Science, Engineering, or a related technical discipline
• Production Systems Experience: Minimum of 2+ years of experience building, shipping, and operating backend or infrastructure systems in production (e.g., distributed services, control planes, schedulers, or observability pipelines)
• Systems Programming Proficiency: Strong engineering fundamentals using a modern systems language such as Go, Rust, or C++
• Shipping Mindset: A strong bias toward action and iterative delivery, favoring practical production software over over-engineered documentation
• Hardware & HPC Familiarity: Hands-on experience or deep familiarity with GPU health telemetry, NVLink/InfiniBand/RoCE networking fabrics, or hardware thermal and power behavior
• Scheduler Internals: Familiarity or direct exposure to Kubernetes internals, Slurm, or other distributed orchestrator ecosystems
• Zero-Trust Security: Knowledge of zero-trust architectures, policy-based access systems, or automated multi-tenant audit streaming

Preferred

• Statistical Methods & ML: Experience applying statistical methods, anomaly detection, or time-series forecasting to noisy operational data for predictive maintenance