Remote: Head of Storage Production Engineering

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 272,000 - 431,000; Full time

Job summary

NVIDIA is seeking a leader for Storage Production Engineering to design, deploy, and operate large-scale storage systems that power AI and HPC workloads. You will build a collaborative, learning-driven team and guide data pipelines and storage technologies across the platform.

You will own capacity planning, high availability, and incident response while partnering with engineering, DevOps, and AI/ML teams to improve performance and reliability.

Qualifications

• BS or MS in Computer Science, Storage Systems, or related field.
• 12+ years in large-scale storage architecture, operations, production engineering, or infrastructure.
• 6+ years of people management or technical leadership in storage, infrastructure, or site reliability teams.
• Experience managing infrastructure operations including on-call rotations, incident response, maintenance, troubleshooting, and optimization of production systems with SLOs/KPIs.
• Hands-on with parallel file systems (Lustre/GPFS), distributed storage (Ceph/MinIO), and S3-compatible/NAS platforms (NetApp, Pure Storage).
• Strong knowledge of block, file, and object storage and HA design.
• Experience with storage networking and protocols (NFS, SMB, iSCSI, Fibre Channel, RDMA, NVMe-oF).
• IaC tooling: Terraform, Ansible, Puppet.
• Knowledge of monitoring/observability tools (Prometheus, InfluxDB, Elastic).

Responsibilities

• Lead and coach a team of Storage Production Engineers.
• Design, deploy, and improve large-scale storage systems (distributed storage, parallel file systems, object storage).
• Use automation, monitoring, and analytics to improve reliability and efficiency of storage services.
• Own capacity planning, data lifecycle management, cost awareness, and high availability/DR plans.
• Evaluate and adopt modern storage approaches (NVMeoF, RDMA, high-speed interconnects, cloud storage).
• Guide incident response and root cause analysis, implementing durable preventive changes.
• Partner with engineering, DevOps, and AI/ML teams to improve data pipelines and workflow performance.

Skills

People management

Storage systems

Incident response

Automation

Monitoring

Capacity planning

SRE principles

Storage protocols

Education

BS or MS in Computer Science, Storage Systems

Tools

Kubernetes

Terraform

Ansible

Puppet

Prometheus

InfluxDB

Elastic stack

Job description

NVIDIA is seeking a leader for Storage Production Engineering to design, deploy, and operate large-scale storage systems that power AI and HPC workloads. You will build a collaborative, learning-driven team and guide data pipelines and storage technologies across the platform.

You will own capacity planning, high availability, and incident response while partnering with engineering, DevOps, and AI/ML teams to improve performance and reliability.