Staff Software Engineer AI Cloud Orchestration (Kubernetes)

Coreweave; Sunnyvale (CA); On-site; USD 207,000 - 275,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with employer match

Paid parental leave

Flexible PTO

Equity awards

Job summary

CoreWeave is seeking a Staff Engineer (IC5) to lead the long-term architecture of its orchestration platform, including SUNK (Slurm on Kubernetes). You will own key components, drive cross-org initiatives in scheduling and scaling, and mentor senior engineers to elevate reliability and performance across hyperscale GPU clusters.

You will shape technical direction, balance cost and reliability, and partner with teams to enable AI workloads at scale.

Qualifications

• 8–12 years of professional software engineering experience.
• Proven track record designing and operating large-scale distributed systems in production.
• Deep expertise in Slurm/Kubernetes internals and cloud-native development.
• Advanced proficiency in Go and distributed systems design.
• Experience setting technical direction and influencing cross-team architecture.
• Ability to mentor senior engineers and elevate organizational standards.

Responsibilities

• Define architectural direction for CoreWeave's orchestration platform and managed services.
• Own critical parts of the platform and drive cross-org initiatives in scheduling and scaling.
• Mentor senior engineers and establish reliability and observability best practices.
• Evolve the orchestration layer to meet next‑gen AI workloads and compute needs.

Skills

Slurm internals

Kubernetes internals

Distributed systems design

Go programming

Technical leadership

Mentoring engineers

Tools

Kubernetes

Slurm

Job description

CoreWeave is seeking a Staff Engineer (IC5) to lead the long-term architecture of its orchestration platform, including SUNK (Slurm on Kubernetes). You will own key components, drive cross-org initiatives in scheduling and scaling, and mentor senior engineers to elevate reliability and performance across hyperscale GPU clusters.

You will shape technical direction, balance cost and reliability, and partner with teams to enable AI workloads at scale.