Senior Storage Engineer, File & Block

CoreWeave•San Francisco, NY

17h

About The Position

CoreWeave is seeking a Senior Storage Engineer, File & Block to join their Storage team. This role is crucial for building and operating the high-performance, multi-tenant file and block storage services that power CoreWeave's AI training and inference workloads, as well as internal stateful services. The engineer will be responsible for the data path and control plane for both file and block storage, operating them on CoreWeave's hardware fleet and developing customer-facing capabilities to support petabyte-scale operations. The position involves close collaboration with compute, platform, and infrastructure teams to ensure 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 like durability, snapshots, replication).
Depth in the storage data path: IO performance, caching, small-file and metadata-heavy workloads, crash consistency, and resilience under load.
Experience with multi-tenant services or storage control planes (provisioning, tenancy/quota, and data-protection features like snapshots, encryption, key management).
Proficiency in a systems/back-end language (Go strongly preferred; C or Rust a plus).
Experience building on Kubernetes (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.
Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).
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

Experience with distributed or parallel storage stacks such as Ceph/RBD, Lustre, GPFS/Spectrum Scale, BeeGFS, WEKA, VAST, or DAOS.
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 services, including 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 GPUs.
Build a native block storage service offering durable, high-performance block volumes for customer workloads and internal stateful services.
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.
Build the control plane, encompassing multi-tenant isolation, quota, QoS, snapshots, key management (BYOK), audit, and lifecycle policy to support regulated and enterprise customers.
Improve the reliability, durability, and observability of the storage stack, partnering with operations to monitor, analyze, and optimize using telemetry, metrics, and dashboards.
Work cross-functionally with platform, product, and infrastructure teams to deliver seamless storage across the stack, including tiering cold data to lower-cost object storage.
Share knowledge and mentor other engineers on best practices in building distributed, high-performance systems.
Work with technologies such as RDMA, GPU Direct Storage, RoCE, InfiniBand, SPDK, and distributed filesystems to optimize storage performance and efficiency.
Collaborate with operations teams to monitor, analyze, and optimize storage systems using telemetry, metrics, and dashboards to improve performance, latency, and resilience.
Share your knowledge and mentor other engineers on best practices in building distributed, high-performance systems.