Staff Software Engineer (AI Workload Orchestration)

Join CoreWeave as a Staff Software Engineer (AI Workload Orchestration) and lead the technical vision and architecture for our AI Workload Orchestration Platform. You will design scalable and reliable orchestration primitives for AI workloads, drive alignment across teams, and mentor senior engineers. This role requires strong proficiency in Go, deep knowledge of Kubernetes internals, and 8+ years of professional software engineering experience.

• Act as a technical leader for CoreWeave’s Kubernetes-native orchestration strategy for AI workloads, defining and evolving the architecture for how AI workloads are admitted, scheduled, and governed across large GPU clusters.
• Own the technical vision and architecture for major portions of the AI Workload Orchestration Platform, designing scalable, reliable orchestration primitives for AI workloads across multiple schedulers and runtimes.
• Lead cross-team architecture reviews and drive alignment across infrastructure, CKS, and managed inference teams, defining platform standards for reliability, observability, capacity management, and operational excellence.

• Strong proficiency in Go and experience designing large-scale, long-lived production systems
• Deep knowledge of Kubernetes internals, scheduling mechanisms, and controller-based architectures
• 8+ years of professional software engineering experience, with deep expertise in distributed systems or cloud platforms
• Strong operational mindset with experience owning mission-critical systems at scale
• Proven ability to lead technical initiatives across teams without direct authority
• Demonstrated experience designing or evolving orchestration, scheduling, or resource-management platforms
• Contributions to open-source infrastructure or orchestration projects
• Experience defining and operating SLOs, capacity models, and large-scale reliability improvements
• Deep understanding of scheduling concepts including fairness, pre-emption, quota management, and multi-tenant isolation
• Background in AI infrastructure, ML platforms, HPC, or large-scale batch and streaming systems
• Hands-on experience with Kueue, Volcano, Ray, or similar Kubernetes-native orchestration frameworks