HPC Storage & Data Engineer for AI-Ready Simulations

WCL Group; Greenville (SC); On-site; USD 72,000 - 80,000; Full time

Job summary

WCL Group is seeking an Application Engineer II to oversee HPC storage and data management for a large cloud-based platform supporting ~1,500 engineers globally. You will manage storage topology, quotas, and access across Linux HPC and Windows VDI environments.

Responsibilities include enforcing permissions, benchmarking storage spend in AWS, and defining data lifecycle policies to optimize data movement from active use to archive for AI/ML readiness.

Qualifications

• Must be able to obtain export authorization from U.S. Government.
• Experience with HPC storage topology, quotas, and archiving.
• Familiarity with multi-protocol storage (NFS/SMB) and access governance.
• Ability to forecast capacity and optimize storage spend in AWS.

Responsibilities

• Manage and optimize HPC storage topology including home, scratch, project, and archive tiers.
• Administer per-user and per-project quotas and monitor utilization trends.
• Enforce file permissions and ACLs across Linux HPC and Windows VDI users.
• Contribute to storage cost benchmarking and reporting in the AWS environment.
• Define data lifecycle policies from active to archive states and automate tiering.
• Collaborate with the DT team to structure shared folders and standard work.

Skills

HPC storage management

AWS cloud

Linux systems

Windows VDI

ACLs and permissions

Storage quotas

Cost benchmarking

Data lifecycle policies

SRE/ops collaboration

Tools

NFS/SMB

VDI environments

Job description

WCL Group is seeking an Application Engineer II to oversee HPC storage and data management for a large cloud-based platform supporting ~1,500 engineers globally. You will manage storage topology, quotas, and access across Linux HPC and Windows VDI environments.

Responsibilities include enforcing permissions, benchmarking storage spend in AWS, and defining data lifecycle policies to optimize data movement from active use to archive for AI/ML readiness.