Software Engineer, Crusoe Energy Systems

• Distributed systems fundamentals: You have a solid grasp of how fault-tolerant distributed systems behave under high load, with experience contributing to such services in production
• A performance mindset: You consider performance in everything you do, bringing hands-on experience profiling and benchmarking real systems, as well as reasoning about the tradeoffs
• A customer-centric mindset: You keep the end-user top of mind, championing decisions that make the platform more reliable for the people who use it
• Technical & infrastructure proficiency: You have strong fundamentals in microservices and cloud-native infrastructure technologies (Docker, Kubernetes, Terraform) alongside languages like Go, Rust, Java, or C++
• Collaboration and communication: You are comfortable working across functions to align on priorities and to explain technical tradeoffs clearly to technical and non-technical partners alike
• Mentorship: You have an interest in helping new teammates onboard onto team systems, as well as helping engineers find their footing and grow
• Experience: 2 - 4 years of professional software development experience, but we care more about what you’ve built than the exact number
• We know great engineers come from many different paths. If you're excited about this work but don't match every point below, we'd still love to hear from you. What you've built and how you think matters more to us than a perfect checklist

Desirable

• We're looking for a Software Engineer II to help make Crusoe Cloud's container registry fast, reliable, and observable at scale. The registry sits on the critical path of every deployment and job launch on our platform, and its performance directly affects how quickly customer workloads come online
• You'll contribute to components of the container registry, with a focus on understanding and improving how the platform performs in production. This is a full-time position
• Build at scale: Contribute to and own components behind Crusoe Cloud's managed container registry, serving the images that training and inference workloads run on
• Ship end-to-end: Own features across the full lifecycle, design, implementation, testing, rollout, and operation
• Tackle hard problems: Take on the hard challenges of building a cloud provider, bringing clarity to ambiguous problems and landing simple, pragmatic designs
• Collaborating across teams: Partner with product and platform teams to align on solutions that serve customers and operations alike
• Build for reliability: Write and ship sustainable software with observability baked in, so the platform stays maintainable as it grows, issues surface early, and root causes are quick to find
• Raise the bar operationally: Spot and act on opportunities to make the team's systems easier, safer, and faster to run