Staff Software Engineer- AI Workload Orchestration

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com .

What You’ll Do:

As a Staff Software Engineer (IC5) on the AI Workload Orchestration Platform team, you will act as a technical leader for CoreWeave’s Kubernetes-native orchestration strategy for AI workloads.

You will define and evolve the architecture for how AI workloads are admitted, scheduled, and governed across large GPU clusters using frameworks such as Kueue, Volcano, and Ray . This platform serves as a strategic complement to SUNK (Slurm on Kubernetes) and underpins both training and inference workloads across the CoreWeave cloud.

This role requires strong systems thinking, cross-team influence, and a long-term view of platform scalability, reliability, and developer experience.

About the role:

• 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 within the organization
• Represent the platform in technical reviews and influence broader CoreWeave platform strategy

Who You Are:

• 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 qualifications:

• 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 sy