Staff Engineer, Storage Engine

About the role

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.

Responsibilities

• Design and Implement distributed storage solutions to support scaling data intensive AI workloads.
• Contribute to the development of exabyte-scale, S3-compatible object storage and integrate dedicated storage clusters into diverse customer environments.
• Work with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency.
• Lead efforts to improve the reliability, durability, security, and observability of our storage stack.
• Collaborate with operations teams to monitor, troubleshoot, and improve storage systems in production environments.
• Set the bar for developing metrics and dashboards to provide visibility into storage performance and health.
• Analyze telemetry and system data to drive improvements in throughput, latency, and resilience.
• Work cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack.
• Share your knowledge and mentor other engineers on best practices in building distributed, high-performance systems.

Requirements

• Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, or a related field.
• 8–10+ years of experience working in storage systems engineering or infrastructure.
• Strong hands-on experience with object storage or distributed filesystems in production environments.
• Experience with one or more storage protocols (e.g. S3, NFS) and file systems such as Ceph, DAOS, or similar.
• Proficiency in a systems programming language such as Go, C, or Rust.
• Proficiency leveraging AI tools to augment software development.
• Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).
• Experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures.