Job Description Summary

Organization's Summary Statement:
The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland is a University-Affiliated Research Center (UARC) dedicated to advancing research, innovation, and technology transition to improve decision making for U.S. national security. ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human-machine teaming. Researchers, scientists, engineers, and analysts at ARLIS collaborate with government agencies, industry partners, and academic institutions to deliver actionable insights and transformative solutions through research and development. Employees at ARLIS work on projects of critical importance, contribute directly to the nation’s security, and are supported by a culture that values integrity, collaboration, and professional growth.

The DevOps Engineer serves as a technical resource for ARLIS, designing, automating, and maintaining secure, reliable cloud and on-premises computing environments that support research and software development, including machine learning and artificial intelligence workloads. The position develops infrastructure as code, automated build and deployment pipelines, and self-service workflows to help researchers obtain and use computing resources efficiently. Working with researchers, software developers, IT staff, and security personnel, the DevOps Engineer maintains development platforms, monitors system performance, resolves operational issues, and implements improvements that support ARLIS research objectives and applicable University and sponsor requirements.

Must be able to obtain a U.S. security clearance. If selected, you must meet the requirements for access to classified information and will be subject to a government security clearance investigation that includes criminal and credit history checks, as well as verification of U.S. citizenship, birth, education, employment, and military history.

KNOWLEDGE, SKILLS, & ABILITIES:
● Knowledge of Azure cloud services and cloud resource lifecycle management, including provisioning, configuration, monitoring, updates, and decommissioning.
● Knowledge of Terraform and Infrastructure as Code principles for repeatable, version-controlled infrastructure deployments.
● Knowledge of Azure DevOps Pipelines and GitHub Enterprise for source control, continuous integration, continuous delivery, and automated testing.
● Knowledge of Sonatype Lifecycle/IQ and Nexus Repository for software composition analysis, policy enforcement, and artifact management.
● Knowledge of ServiceNow and the integration of requests, approvals, and fulfillment activities into automated or self-service workflows.
● Knowledge of Rancher, Docker, Kubernetes, and on-premises GPU infrastructure, including NVIDIA drivers and containerized GPU workloads.
● Knowledge of Datadog or comparable observability platforms for metrics, logs, dashboards, monitoring, and alerting.
● Knowledge of networking fundamentals and the application of cloud security best practices.
● Skill in the use of integrating enterprise platforms through REST and GraphQL APIs, webhooks, vendor SDKs, and command-line interfaces.
● Skill in the use of Linux and Windows Server configuration, troubleshooting, and optimization.
● Skill in the use of software development practices, including version control, testing, documentation, and maintainable automation, with an operational mindset.
● Ability to design, build, and maintain CI/CD pipelines, process automation, and self-service infrastructure workflows.
● Ability to communicate technical information effectively in oral and written form and provide customer-focused service.
● Ability to interpret and apply policies, procedures, regulations, and laws.
● Ability to manage multiple priorities while supporting production and development services.

Minimum Qualifications:

Education: Master’s degree from an accredited college or university.

Experience: Three (3) years of professional experience in systems engineering, cloud infrastructure, or DevOps engineering.

Other: Additional work experience as defined above may be substituted on a year for year basis for up to four (4) years of the required education.

Physical Demands:
Sedentary work performed in a normal office environment; exerts up to 10 pounds of force occasionally and/or negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Ability to attend meetings both on and off campus. Spending long hours in front of a computer screen.


Licenses/ Certifications: N/A

Additional Job Details

Preferences:

Education:

● Degree in Computer Science, Software Engineering, or a related field

Experience:

● Experience providing technical guidance or mentoring colleagues in DevOps tools, automation, or software delivery practices.

● Experience supporting research computing, ML/AI workloads, or shared GPU infrastructure.

● Experience delivering technical projects independently and collaboratively while managing competing priorities.

Required Application Materials: Cover Letter, Resume, List of References

 

Best Consideration Date: 11/6/26

 

Posting Close Date: N/A

 

Open Until Filled:Yes

 

Financial Disclosure Required

No

Department

VPR-Applied Research Lab for Intelligence & Security

Worker Sub-Type

Faculty Regular

Salary Range

$140,000 - $177,966

Background Checks

Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.

Employment Eligibility

The successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization.  Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.

EEO Statement

The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy.

Title IX Non-Discrimination Notice

Resources

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