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Senior Software Engineer II, AI Workload Orchestration

CoreWeave
CompanyCoreWeave
CategoryUncategorised
LocationSunnyvale
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted23 Jan 2026
Last verified9 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
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 Senior Software Engineer II (IC4) on the  AI Workload Orchestration  team, you will help build and operate CoreWeave’s Kubernetes-native platform for admitting, scheduling, and operating AI workloads at scale. This platform integrates multiple orchestration and scheduling frameworks such as Kueue, Volcano, and Ray to support modern AI training and inference workflows. It complements SUNK (Slurm on Kubernetes) by providing a Kubernetes-first, cloud-native orchestration layer with deep platform integration. You will own meaningful components of the platform, drive reliability and performance improvements, and help scale the system as customer demand and workload complexity continue to grow. About the role: Design, build, and operate Kubernetes-native services for AI workload orchestration and scheduling Own one or more platform components end-to-end, including design, implementation, testing, and on-call support Improve scheduling latency, cluster utilization, and workload reliability through metrics-driven engineering Contribute to architectural discussions across services and influence design decisions within the platform Work closely with adjacent teams (CKS, infrastructure, managed inference) to ensure clean interfaces and integrations Mentor junior engineers and raise the quality bar for code, design, and operations Who You Are: 5–8 years of professional software engineering experience in distributed systems, cloud infrastructure, or platform engineering Strong experience building production systems in Go (Python or C++ a plus) Solid understanding of Kubernetes fundamentals , APIs, controllers, and operating services in production Experience working with scheduling, resource management, or quota-based systems Proven ability to improve system reliability and performance using data and operational metrics Comfortable owning services in production and participating in on-call rotations Preferred: Experience with Kubernetes-native orchestration frameworks such as Kueue, Volcano, Ray, Kubeflow, or Argo Workflows Familiarity with GPU-based workloads, ML training, or inference pipelines Knowledge of scheduling concepts such as quota enforcement, pre-emption, and backfilling Experience with reliability practices including SLOs, alerting, and incident response Exposure to AI infrastructure, HPC, or large-scale distributed compute environments Wondering if you’re a good fit? We believe in investing in our people and value candidates who can bring their diverse experiences to our teams – even if you aren't a 100% skill or experience match. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:  Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. A