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Crusoe

Software Engineer II, Crusoe Container Registry

San Francisco, CA - USfulltimemidAdded today

About this role

Crusoe seeks a Software Engineer II to build and operate a high-performance container registry that serves as a critical component of their AI cloud platform. You'll own features end-to-end, focus on reliability and observability at scale, and collaborate with product and platform teams to ensure fast deployment and job launch times.

What you'll do

  • Own and contribute to components of Crusoe Cloud's managed container registry serving training and inference workloads
  • Ship end-to-end features including design, implementation, testing, rollout, and operational monitoring
  • Solve distributed systems challenges at scale with emphasis on performance and reliability
  • Collaborate with product and platform teams to align on customer-centric solutions
  • Build sustainable software with observability built in to maintain platform health as it grows
  • Identify and implement operational improvements to make systems easier, safer, and faster to run

What they're looking for

  • Distributed systems design and fault tolerance under high load
  • Performance profiling, benchmarking, and optimization
  • Microservices and cloud-native infrastructure (Docker, Kubernetes, Terraform)
  • Programming in Go, Rust, Java, or C++
  • Container technologies and OCI image specifications
  • Storage or caching systems at scale
  • Cross-functional collaboration and technical communication
  • Mentorship and onboarding of new team members

Benefits

  • Competitive compensation and equity
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Crusoe

Crusoe builds AI infrastructure and data center systems, including cloud platforms, modular facilities, and manufacturing operations. The company is hiring engineers across software, mechanical engineering, facilities management, instrumentation, and CNC programming to design, optimize, and operate its mission-critical infrastructure.

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Likely interview questions

  • Describe a time you optimized a distributed system's performance in production—what bottleneck did you identify and how did you approach solving it?
  • How do you approach designing for reliability and observability in systems that sit on critical deployment paths?
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