CoreWeave is The Essential Cloud for AI™, a publicly traded company (Nasdaq: CRWV) since March 2025
Delivers a platform of technology, tools, and teams enabling innovators to build and scale AI
About the role
Staff Software Engineer (IC5) on the AI Workload Orchestration Platform team
Act as technical leader for CoreWeave's Kubernetes-native orchestration strategy for AI workloads
Define and evolve architecture for how AI workloads are admitted, scheduled, and governed across large GPU clusters using frameworks such as Kueue, Volcano, and Ray
Platform serves as strategic complement to SUNK (Slurm on Kubernetes) and underpins training and inference workloads
Responsibilities
Own the technical vision and architecture for major portions of the AI Workload Orchestration Platform
Design 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
Define platform standards for reliability, observability, capacity management, and operational excellence
Identify and resolve systemic performance, scalability, and fairness issues across large GPU clusters
Mentor senior engineers and grow technical leadership
Requirements
8+ years of professional software engineering experience with deep expertise in distributed systems or cloud platforms
Strong proficiency in Go and experience designing large-scale, long-lived production systems
Deep knowledge of Kubernetes internals, scheduling mechanisms, and controller-based architectures
Demonstrated experience designing or evolving orchestration, scheduling, or resource-management platforms
Proven ability to lead technical initiatives across teams without direct authority
Strong operational mindset with experience owning mission-critical systems at scale
Preferred
Hands-on experience with Kueue, Volcano, Ray, or similar Kubernetes-native orchestration frameworks
Background in AI infrastructure, ML platforms, HPC, or large-scale batch and streaming systems
Deep understanding of scheduling concepts including fairness, pre-emption, quota management, and multi-tenant isolation
Experience defining and operating SLOs, capacity models, and large-scale reliability improvements
Contributions to open-source infrastructure or orchestration projects
Conditions
Base salary range: $188,000 to $275,000
Total rewards package includes discretionary bonus, equity awards, and comprehensive benefits program