Austen Portz
About Austen Portz
Austen Portz serves as the Senior Vice President of Engineering at Sonic Foundry Inc., where he has worked since 2019. He has a background in Electrical Engineering from the University of Wisconsin-Madison and has played a key role in transitioning engineering teams to agile methodologies while leading the development of innovative video technology solutions.
Work at Sonic Foundry
Austen Portz has been with Sonic Foundry Inc. since 2003, progressing through various roles over the years. He currently serves as the Senior Vice President of Engineering, a position he has held since 2019. Prior to this role, he was Vice President of Engineering from 2017 to 2019. His earlier positions at Sonic Foundry include Director of Hardware Engineering, Hardware Engineering Manager, and Hardware Engineer. He also gained initial experience as an Operations Intern, Systems Intern, and IT Intern during his studies.
Education and Expertise
Austen Portz earned a Bachelor of Science degree in Electrical Engineering from the University of Wisconsin-Madison, where he studied from 2002 to 2006. His educational background provides a strong foundation for his technical expertise in engineering, product development, and technology management.
Background
Austen Portz has extensive experience in engineering and technology roles, particularly within Sonic Foundry Inc. His career spans nearly two decades, during which he has transitioned various teams to agile methodologies, specifically the Scrum framework. He has also led initiatives in DevOps, focusing on improving software delivery performance.
Achievements
Portz has led significant projects at Sonic Foundry, including the development and continuous improvement of the Mediasite Video Platform, which serves various sectors globally. He envisioned and developed Mediasite Mosaic, a multi-track video recording application, and spearheaded the creation of Vidable, an AI-enabled video transformation service. Additionally, he formed an Advanced Research team dedicated to exploring artificial intelligence and machine learning for audiovisual enhancement.