HPC Systems Engineer

Charlottesville, VA, US • Posted 4 hours ago • Updated 4 hours ago
Full Time
On-site
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Job Details

Skills

  • High Performance Computing
  • Computational Science
  • Performance Analysis
  • Storage
  • Network
  • Provisioning
  • xCAT
  • Scheduling
  • GRID
  • Workflow
  • Linux Administration
  • Red Hat Enterprise Linux
  • Parallel Computing
  • MPI
  • OpenMP
  • Docker
  • Remote Direct Memory Access
  • InfiniBand
  • Computer Networking
  • Communication
  • Writing
  • System Administration
  • Science
  • Security Clearance
  • Linux
  • Command-line Interface
  • Interfaces
  • Scripting
  • Bash
  • Python
  • Management
  • HPC
  • Distributed File System
  • IBM GPFS
  • GPU
  • CUDA
  • Configuration Management
  • Ansible
  • Puppet
  • Research
  • DoD
  • IC
  • Internal Communications
  • Integrated Circuit
  • Information Technology
  • Systems Engineering
  • FOCUS

Summary

Job ID: 2610670

Location: Charlottesville, VA, US

Date Posted: 2026-03-26

Category: Engineering and Sciences

Subcategory: Systems Engineer

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: Top_Secret

Clearance Level Must Be Able to Obtain: TS/SCI

Potential for Remote Work: ORA_ON_SITE

Description

SAIC is looking for a highly qualified HPC Systems Engineer to support the Army's Golden Dome initiative. The engineer will support the deployment and sustainment of Linux-based High Performance Computing (HPC) cluster environments used for distributed compute workloads, simulation environments, and GPU-enabled processing.

The environment will include:
  • multi-node Linux compute clusters
  • workload scheduling platforms such as Slurm or PBS
  • cluster provisioning frameworks (e.g., xCAT, Warewulf)
  • high-performance networking technologies including RDMA / InfiniBand
  • distributed parallel compute workloads utilizing MPI or OpenMP
  • GPU-enabled compute resources supporting CUDA-based processing


The system will be used to support scientific computing, simulation workloads, and other distributed compute operations within a secure research environment.

Candidates should be comfortable working within cluster-scale computing environments where performance, scheduler configuration, and distributed workload execution are critical operational factors.

The HPC Systems Engineer will support the build-out, configuration, and sustainment of HPC cluster platforms.

The role focuses on:
  • cluster platform configuration
  • scheduler administration
  • distributed compute troubleshooting
  • performance analysis across compute, storage, and network layers
  • GPU compute workload support
  • automation and operational tooling


Candidates should have experience working with multi-node Linux cluster environments and distributed compute workloads.

Core Technical Capabilities

Candidates should demonstrate capability in most of the following areas.

HPC Cluster Platforms

Experience supporting multi-node Linux compute clusters, including node integration, configuration, and operational sustainment.

Experience with cluster provisioning tools such as xCAT, Warewulf, or similar node deployment systems is beneficial.

Workload Scheduling Platforms

Experience supporting distributed compute workloads using schedulers such as:
  • Slurm
  • PBS / PBS Pro
  • Torque
  • Grid Engine


Candidates should understand queue configuration, job submission workflows, and scheduler troubleshooting.

Candidates should understand how workload schedulers interact with distributed compute workloads and containerized execution environments.

Linux Systems Administration

Strong Linux administration experience including:
  • command-line system administration
  • server and compute node configuration
  • system troubleshooting in distributed compute environments


Experience with RHEL-based environments is preferred.

Distributed and Containerized Workloads

Experience supporting distributed compute workloads utilizing parallel computing frameworks such as:
  • MPI
  • OpenMP
  • GPU compute frameworks


Candidates should understand how workload schedulers interact with distributed compute workloads and containerized execution environments within HPC clusters.

Familiarity with container technologies commonly used in HPC environments such as:
  • Docker
  • Podman
  • Singularity / Apptainer


Candidates should understand how containerized workloads interact with schedulers, GPU resources, and distributed compute environments.

Experience supporting containerized HPC workloads or integrating container platforms with cluster infrastructure is desirable.

HPC Networking

Familiarity with high-performance networking technologies including:
  • RDMA networking
  • InfiniBand
  • high-throughput cluster networking architectures


Candidates should be comfortable assisting with troubleshooting cluster communication or performance issues.

GPU Compute Environments

Experience supporting GPU-enabled compute environments and workloads utilizing CUDA frameworks is desirable.

Automation and Operational Tooling
Experience writing scripts or operational tooling using languages such as:
  • Bash
  • Python

Automation experience supporting system administration or cluster operations is beneficial.

Qualifications

Candidates must meet the following requirements:
  • Bachelor degree in science/technology; 10 additional YoE can be substituted for degree
  • 8+ years of experience is required
  • Minimum 6 years of experience administering Linux systems in enterprise, research computing, or distributed compute environments
  • An Active Top Secret clearance is required; an active TS/SCI clearance must be obtained prior to beginning work.
  • 100% onsite support in Charlottesville, VA
  • Experience supporting distributed compute environments or HPC cluster platforms
  • Experience working with workload schedulers such as Slurm, PBS, Torque, or similar systems
  • Experience administering Linux systems through command-line interfaces
  • Experience with scripting or automation tools (Bash, Python, or similar)
  • Ability to obtain required DoD 8140 (8570) IAT Level II certification
  • Candidates must have direct experience with HPC or distributed compute environments.

Candidates with the following experience are strongly preferred:
  • Administration of multi-node HPC cluster environments
  • Experience with parallel or distributed file systems such as Lustre, BeeGFS, or GPFS
  • Experience supporting GPU-enabled compute environments and CUDA workloads
  • Experience with configuration management tools such as Ansible or Puppet
  • Experience supporting research, laboratory, or mission computing environments
  • Experience supporting systems within DoD/DoW or IC environments



Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10111346
  • Position Id: 2610670
  • Posted 4 hours ago

Company Info

About SAIC

SAIC® is a premier Fortune 500 mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, civilian and intelligence markets include secure high-end solutions in mission IT, enterprise IT, engineering services and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 24,000 strong; driven by mission, united by purpose, and inspired by opportunities. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.5 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

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