Senior Research Infra Engineer — AI, HPC & Cloud

Clayton State University; Georgia; On-site; USD 95,000 - 121,000; Full time

Job summary

Augusta University is recruiting a Senior Research Infrastructure Engineer to design, build, and operate secure, scalable infrastructure for research computing, HPC, and AI initiatives. The role focuses on compute, storage, networking, data center services, GPU resources, and AI-enabled environments to support data-intensive workloads.

The position leads capacity planning, performance optimization, and operational readiness, enabling AI-driven research and secure integration of emerging

Qualifications

• Bachelor's degree or equivalent plus six years of experience in research computing or systems administration.
• Experience with cloud, hybrid, and on‑premises infrastructure for research tech/data services.
• Proficiency with scripting, automation, monitoring, version control, and related tools.

Responsibilities

• Design, implement, maintain, and optimize infrastructure for research computing, HPC, AI workloads, storage, backup, and related services.
• Maintain technical documentation, configuration records, architecture documentation, and procedures.
• Collaborate with researchers, faculty, vendors, and IT staff to deliver technical solutions aligned with research priorities.

Skills

Linux/Unix administration

Scripting & automation

Cloud & hybrid infrastructure

Security & compliance

Storage & backup

Networking basics

Documentation & communication

Education

Bachelor's degree from an accredited college or university

Six years of experience in research computing or systems administration

Tools

Terraform

Ansible

Git

Cloud platforms (AWS/Azure/GCP)

Job description

Augusta University is recruiting a Senior Research Infrastructure Engineer to design, build, and operate secure, scalable infrastructure for research computing, HPC, and AI initiatives. The role focuses on compute, storage, networking, data center services, GPU resources, and AI-enabled environments to support data-intensive workloads.

The position leads capacity planning, performance optimization, and operational readiness, enabling AI-driven research and secure integration of emerging