EU remote
Staff Engineer, AI Object Storage
About this role
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 . We're proud to be a Living Wage accredited Employer. What You'll Do: The Storage Engine Team at CoreWeave is responsible for the product capabilities and data plane function of CoreWeave’s managed storage products. We build reliable, scalable storage solutions with segment-leading performance, collaborating across infrastructure, compute, and platform teams to meet the needs of the world’s most demanding AI workloads.
About the role: As a Staff Engineer, AI Object Storage, you will design and implement distributed storage solutions to support scaling data-intensive AI workloads. You will contribute directly to the development of exabyte-scale, S3-compatible object storage and integrate dedicated clusters into diverse customer environments. Operating across hardware-adjacent stacks, you will leverage technologies like RDMA, GPU Direct Storage, and distributed filesystem protocols (e.g., NFS, FUSE) to optimise throughput, tail latency, and overall efficiency.
Additionally, you will lead cross-functional efforts to elevate reliability, durability, security, and telemetry metrics while establishing operational best practices, architectural standards, and technical mentorship across the engineering team. Who You Are: Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience). 8+ years of professional engineering experience in storage systems engineering or infrastructure platforms.
Strong hands-on experience with object storage or distributed filesystems in high-scale production environments. Deep experience with storage protocols (e.g., S3, NFS) and distributed architectures such as Ceph, DAOS, or similar. Proficiency in a systems programming language such as Go, C, or Rust. Experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures. Familiarity with storage observability, metrics collection, and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).