Job Description Summary:

This position is available within the University of Maryland’s Division of Information Technology (DIT).

Join the forefront of technological innovation by becoming an AI Engineer within the Division of Information Technology (DIT) at the University of Maryland. From conceptual ideation to production-grade AI applications, you will work with a talented group of engineers to develop scalable AI frameworks and solutions that are robust and uphold the highest standards of quality and innovation. The ideal candidate for this role should be a highly skilled developer experienced in using Jira for task and milestone management. Proven ability to deliver project updates on schedule is essential. This hands-on role requires strong data management abilities, an understanding of Machine Learning and AI Principles, and hands-on experience with Azure cloud technologies. They will operate in a DevOps environment to automate, test, monitor, and push releases across cloud environments.

Be a part of a visionary team dedicated to enhancing the University of Maryland's educational and operational excellence through technological innovation. Your work as an AI Engineer
will pave the way for groundbreaking advancements supporting the University’s research, teaching, and services mission.

**This position is considered essential and may be required to work at the normal work location or an alternative location during a major catastrophic event, weather emergency, or other operational emergency to help maintain the continuity of University services.**

**May be required to work evenings, nights, weekends, or different shifts for extended periods.**

Physical Demands:

Sedentary work. Employee will need to be able to sit for long periods of time to work on a computer, as well as travel occasionally to meet with clients and customers on and off campus. This position is considered an essential position and may be required to work at the normal work location or an alternative location during a major catastrophic event, weather emergency, or other operational emergencies to help maintain continuity of University services.

Preferences:

• Experience supporting production Generative AI or AI-enabled solutions in an enterprise cloud environment.

• Experience with Azure operations, including support, maintenance, monitoring, troubleshooting, and administration of cloud-hosted services.

• Experience managing operational workloads involving queues, asynchronous processing, integrations, and system reliability.

• Experience supporting COTS, SaaS, or vendor-supported platforms, including upgrades, issue resolution, and coordination with external partners.

• Experience supporting RAG-based solutions, including knowledge base administration, document ingestion, indexing, and vector data stores.

• Experience developing scripts and automation to support deployments, system maintenance, operational workflows, and service reliability.

• Experience with CI/CD pipelines, infrastructure as code, automated testing, and release support for enterprise cloud applications.

• Experience creating runbooks, knowledge documentation, and support procedures for technical operations and service sustainment.

• Experience with monitoring, logging, alerting, and incident response practices for cloud and AI-enabled systems.

• Experience working in a collaborative DevOps, SRE, or cloud operations environment supporting both technical and non-technical stakeholders.

Additional Information: 
Please note that all positions within the Division of Information Technology (DIT) have an in person component with expected time in our College Park, MD location per week. Telework is not a guaranteed work arrangement.

Visa Sponsorship Information:

• DIT will not sponsor the successful candidate for work authorization in the United States now or in the future..

• F1 STEM OPT support is not available for this position

Required Application Materials:

Resume 
Cover Letter
List of three References

Best Consideration Date:

05/06/2026

Posting Close Date:

Open Until Filled

Open Until Filled:

Yes