Job Description

Job Description

Reporting to the Director for IT Operations , the Systems Engineer, designs, builds, and maintains on-premise and cloud-based infrastructure supporting library systems and research computing. Maintains production services including repository platforms, search and indexing systems, metadata pipelines (including ML/AI-driven metadata generation workflows), and associated data stores. Develops automated deployment and configuration workflows using infrastructure-as-code and configuration management practices, ensuring that systems are configured and operated in accordance with university policy and standard security practices. Supports containerized services and contributes to deployment practices and orchestration platforms. Works with library faculty to provision and maintain computational environments, including GPU-backed systems for machine learning workloads.

Required Qualifications

-Bachelor’s degree in computer science, computer engineering, information science, or a related field, (or a Bachelor’s in another field with equivalent professional experience directly related to the position).
-Experience administering Linux-based systems, including networking, security practices, and system performance management, as demonstrated through professional experience, academic coursework, or applied projects.
-Experience with version control workflows using Git in a collaborative environment, including branching strategies, pull requests, code review, and integration with CI/CD pipelines in team-based projects.
-Demonstrated scripting experience in languages such as Bash, Python, or Powershell for automation and systems integration. Evidence may include development of scripts or small utilities that automate system administration tasks, interact with APIs, or support data or metadata processing workflows.
-Experience deploying and managing containerized applications using Docker, including building images, defining services with Dockerfiles or Compose, managing multi-service deployments, and troubleshooting containerized environments.
-Experience working independently and in coordination with other engineers on diagnosing and resolving system-level issues, debugging production or lab environments, analyzing logs and system metrics.

Preferred Qualifications

-Experience supporting research computing or digital scholarship environments, including repository systems, metadata workflows, or data/ML processing pipelines.
-Experience with cloud services, including compute, networking, and storage (e.g., S3, Glacier).
-Experience building or maintaining CI/CD pipelines (e.g., GitLab CI or similar systems).
-Experience with infrastructure-as-code concepts and tools (e.g., Terraform or equivalent).
-Experience with centralized logging and monitoring platforms (e.g., Splunk or equivalent).
-Experience working with storage systems, including network-attached storage or distributed storage platforms (e.g., TrueNAS, Ceph).
-Experience supporting GPU-backed compute environments for machine learning training or inference workloads.