Staff Software Engineer- AI Workload Orchestration

<div class="content-intro"><div> <div> <div class="gmail_quote"> <div> <div><span id="m_1770241969069985273m_-2746164444908759431gmail-docs-internal-guid-131e4fb0-7fff-b4e9-ff50-e8cf32449b1b">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&nbsp;<a href="http://www.coreweave.com/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=http://www.coreweave.com&amp;source=gmail&amp;ust=1762613132717000&amp;usg=AOvVaw3D-UOhNaqEvF5BEWxjYyAU">www.coreweave.com</a>.</span></div> </div> </div> </div> </div></div><h3><span style="text-decoration: underline;"><strong>What You’ll Do:</strong></span></h3> <p>As a <strong>Staff Software Engineer (IC5)</strong> on the <strong>AI Workload Orchestration Platform</strong> team, you will act as a technical leader for CoreWeave’s Kubernetes-native orchestration strategy for AI workloads.</p> <p>You will define and evolve the architecture for how AI workloads are admitted, scheduled, and governed across large GPU clusters using frameworks such as <strong>Kueue, Volcano, and Ray</strong>. This platform serves as a strategic complement to <strong>SUNK (Slurm on Kubernetes)</strong> and underpins both training and inference workloads across the CoreWeave cloud.</p> <p>This role requires strong systems thinking, cross-team influence, and a long-term view of platform scalability, reliability, and developer experience.</p> <h3><span style="text-decoration: underline;"><strong>About the role:</strong></span></h3> <ul> <li>Own the technical vision and architecture for major portions of the AI Workload Orchestration Platform</li> <li>Design scalable, reliable orchestration primitives for AI workloads across multiple schedulers and runtimes</li> <li>Lead cross-team architecture reviews and drive alignment across infrastructure, CKS, and managed inference teams</li> <li>Define platform standards for reliability, observability, capacity management, and operational excellence</li> <li>Identify and resolve systemic performance, scalability, and fairness issues across large GPU clusters</li> <li>Mentor senior engineers and grow technical leadership wit