Staff Software Engineer

• Crusoe is on a mission to accelerate the abundance of energy and intelligence by building the world’s only vertically integrated AI infrastructure company from the ground up
• As a Software Engineer on the Cloud Availability Platform team, you will help build Conductor—our self-driving control plane designed to predict, decide, and act autonomously to keep tens of thousands of accelerators running at peak efficiency
• In this role, you will play a direct part in solving the AI compute energy bottleneck by treating power as a control input rather than a static constraint
• Working alongside staff and principal engineers, you will have true ownership over greenfield services, building distributed systems that optimize power, cost, and useful compute in real time
• This is a full-time position tailored for a problem-solving engineer who thrives in ambiguity and has a strong bias toward shipping
• You will tackle rare infrastructure challenges—such as energy-aware compute scheduling, closed-loop remediation, and failure prediction on noisy hardware telemetry—transforming complex operational signals into a single, programmable control plane
• Core Responsibilities: Design, build, and operate greenfield distributed services, control planes, and closed-loop remediation systems that automatically drain, checkpoint, replace, and resume live AI workloads without manual intervention
• Communication & Collaboration: Partner closely with staff and principal engineers to review architectures, establish safety rails for autonomous operations, and share technical knowledge across the cloud services team
• Daily Interactions: Collaborate daily with cross-functional partners spanning hardware engineering, energy management, data center construction, and customer support to align system design with physical infrastructure
• Key Contributions: Own the development of core platform features such as unified observability pipelines, energy-aware compute scheduling, straggler detection, and self-qualifying hardware pipelines to maximize overall system goodput

Benefits

• Health & wellbeing: Comprehensive health benefits designed to support your overall wellness
• Time away: Paid time off for vacations, family bonding, and unexpected needs
• 401(k) match: Build your financial future with our 401(k) matching program
• Mental wellness: Resources and support for your emotional wellbeing and navigating life’s challenges- 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
• 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
• Distributed Systems Foundations: Demonstrated mastery of state reconciliation, retries and idempotency, consistency tradeoffs, and autonomous automation on live infrastructure
• Hardware & HPC Familiarity: Hands-on experience or deep familiarity with GPU health telemetry, NVLink/InfiniBand/RoCE networking fabrics, or hardware thermal and power behavior
• Observability Architecture: Prior experience designing scalable observability and telemetry pipelines that span compute, storage, and networking layers
• Scheduler Internals: Familiarity or direct exposure to Kubernetes internals, Slurm, or other distributed orchestrator ecosystems
• Statistical Methods & ML: Experience applying statistical methods, anomaly detection, or time-series forecasting to noisy operational data for predictive maintenance
• Zero-Trust Security: Knowledge of zero-trust architectures, policy-based access systems, or automated multi-tenant audit streaming