Media Systems Engineer

What You’ll Do

The Center for Academic Innovation (CAI) at the University of Michigan (U‑M) seeks a skilled Media Systems Engineer to lead the technical development and integration of media asset workflows, storage, and retrieval systems. This role will utilize various techniques, including programming and Generative AI, to enhance operational efficiency across CAI’s media asset management systems for online learning, XR programs, and digital archives.

As a Media Systems Engineer, you will develop custom applications, automate workflows, and integrate AI‑powered solutions, directly collaborating with CAI’s Media Technology, Media Design, and XR teams. You will be responsible for implementing scalable solutions that leverage a range of technologies, including generative AI, to improve media production and data management processes. You will serve as CAI’s technical lead and system owner for the enterprise MAM solution, representing the center in vendor selection, implementation, governance, and ongoing operations.

This position will report to the Director of Technology Infrastructure and Support.

• Serve as the technical owner of CAI’s enterprise Media Asset Management (MAM) platform, responsible for its reliability, scalability, and long‑term evolution.
• Design, implement, and maintain software, automation, and integrations that support media asset management workflows and daily operations.
• Define and maintain metadata schemas, taxonomies, and asset structures to ensure media assets are discoverable, reusable, and durable over time.
• Lead MAM governance collaboratively with creative, technical, and operational stakeholders, ensuring governance decisions are consistently implemented in systems and workflows.
• Design, document, and maintain end‑to‑end media workflows spanning ingest, production, review, distribution, and long‑term archival.
• Implement automation and system improvements to increase efficiency, consistency, and quality across media production and asset management processes.
• Evaluate and implement AI‑assisted capabilities (e.g., automated tagging, transcription, search, analytics) using a human‑in‑the‑loop approach to maintain accuracy and trust.
• Manage and evolve media storage, backup, and archival solutions, supporting the transition from legacy systems to modern, scalable architectures.
• Design and support integrations between the MAM platform and related systems, including storage, editing tools, learning platforms, and archival environments.
• Lead onboarding, documentation, and training to support adoption of MAM workflows, tools, and AI‑assisted processes.
• Continuously assess emerging media technologies and tools, recommending and implementing solutions that support CAI’s long‑term production and data management needs.

• Bachelor’s degree in Computer Science, Information Science, Media or Broadcast Technology, Business Systems Administration, Library and Information Sciences, or a related field, or equivalent professional experience.
• A minimum of 2–4 years of professional experience in a media‑rich technical environment, with demonstrated responsibility for complex systems, workflows, or platforms.
• Experience in software development, automation, or scripting, with proficiency in Python, JavaScript, or a similar language, applied to system integration, workflow automation, or platform support.
• Experience working with or supporting APIs, system integrations, and cloud‑based platforms (e.g., AWS, Azure, or Google Cloud), or a demonstrated ability to quickly learn these technologies.
• Experience with media production environments and media or digital asset management systems (MAM/DAM), including an understanding of how technical systems support creative workflows.
• Working knowledge of media storage, backup, and archival practices, including networked storage and long‑term data retention; experience supporting or migrating archival systems is welcome.
• Demonstrated interest in and practical use of emerging technologies, including automation and AI‑assisted tools, to improve workflows, data quality, and system reliability.
• Strong problem‑solving skills and the ability…