Key responsibilities include:

• Designing and implementing distributed storage solutions to support scaling data-intensive AI workloads
• Contributing to the development of exabyte-scale, S3-compatible object storage
• Integrating dedicated storage clusters into diverse customer environments
• Working with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency
• Leading efforts to improve the reliability, durability, security, and observability of the storage stack
• Collaborating with operations teams to monitor, troubleshoot, and improve storage systems in production environments
• Setting the bar for developing metrics and dashboards to provide visibility into storage performance and health
• Analyzing telemetry and system data to drive improvements in throughput, latency, and resilience
• Working cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack
• Sharing knowledge and mentoring other engineers on best practices in building distributed, high-performance systems

Requirements include:

• 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

The base salary range for this role is $188,000 to $275,000.

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