Senior Engineer, Storage (File & Block)

CoreWeave•Sunnyvale, CA

48d•$182,000 - $242,000

About The Position

CoreWeave is seeking a Senior Storage Engineer, File & Block to build and operate the file and block storage services at the heart of CoreWeave's Storage team. This role is crucial for developing high-performance, multi-tenant storage essential for AI training and inference workloads, as well as internal stateful services. The engineer will focus on enhancing CoreWeave's storage capabilities to be a multiplier of GPU growth by owning the data path and control plane for both file and block storage, operating them on their own hardware fleet, and delivering customer-facing features that support large-scale deals. Collaboration with compute, platform, and infrastructure teams is key to ensuring storage is fast, reliable, and easy to use at scale.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
6–10 years of experience building storage systems, distributed systems, or infrastructure services.
Strong hands-on experience with distributed or networked file systems and/or block storage in production (e.g., NFS/POSIX file semantics at scale, and/or block volume services with durability, snapshots, replication).
Depth in the storage data path, including IO performance, caching, small-file and metadata-heavy workloads, crash consistency, and resilience under load.
Experience with multi-tenant services or storage control planes, including provisioning, tenancy/quota, and data-protection features (snapshots, encryption, key management).
Proficiency in a systems/back-end language, with Go strongly preferred (C or Rust a plus).
Experience building on Kubernetes, including controllers/operators, CRDs, and CSI (dynamic provisioning, resize, snapshots, RWO volumes).
Familiarity with distributed databases (e.g., CockroachDB), workflow orchestration (e.g., Temporal), and gRPC/Protobuf service design.
Strong debugging and problem-solving skills in distributed, high-performance environments.
Clear communicator, able to work collaboratively across teams and share technical insights effectively.

Nice To Haves

Ideally, experience with distributed or parallel storage stacks such as Ceph/RBD, Lustre, GPFS/Spectrum Scale, BeeGFS, WEKA, VAST, or DAOS.
Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).
Bonus: exposure to high-performance data-path technologies (RDMA, GPUDirect Storage, RoCE, InfiniBand, SPDK).

Responsibilities

Design, build, and operate highly scalable, multi-tenant file and block storage, covering both the data path (NFS for file; durable, high-performance block volumes) and the control plane for tenancy, provisioning, and data protection, running natively on CoreWeave's storage fleet and delivered through Kubernetes.
Own the file system data path, focusing on NFS hot-path reliability, IO resilience, and performance, particularly for small-file/IOPS-heavy workloads critical for AI pipelines and throughput for feeding GPUs.
Build a native block storage service offering durable, high-performance block volumes for customer workloads and internal stateful services, integrating it into the file/object/block triad and running on shared storage hardware.
Deliver both file and block storage as first-class Kubernetes citizens by designing and shipping a backend-neutral CSI driver with dynamic provisioning, resize, snapshots, and RWO block volumes, backed by a public provisioning SLO, and reusing shared control-plane and CSI patterns.
Build the control plane, encompassing multi-tenant isolation, quota, QoS, snapshots, key management (BYOK), audit, and lifecycle policy to support regulated and enterprise customers with features like encryption in transit and HIPAA controls.
Improve the reliability, durability, and observability of the storage stack by partnering with operations to monitor, analyze, and optimize using telemetry, metrics, and dashboards to enhance performance, latency, and resilience.
Collaborate cross-functionally with platform, product, and infrastructure teams to ensure seamless storage across the stack, including tiering cold data to lower-cost object storage while maintaining access.
Share knowledge and mentor other engineers on best practices for building distributed, high-performance systems.