Bennet Huber
About Bennet Huber
Bennet Huber is the Chief Software Architect at Compose AI, with a strong background in microservice architectures and high-performance computing. He has extensive experience in software development, particularly in backend cloud architecture and natural language processing applications.
Current Role at Compose AI
Bennet Huber serves as the Chief Software Architect at Compose AI, a position he has held since 2021. In this role, he focuses on developing advanced software solutions and architecture, leveraging his extensive experience in backend cloud architecture. His work emphasizes natural language processing applications, aligning with the company's goals in AI development.
Previous Experience at Amazon
Bennet Huber has a significant tenure at Amazon, where he worked in various capacities. He began as a Software Development Engineer from 2014 to 2016, followed by a role as Software Development Engineer 2 from 2016 to 2019. He continued in this position until 2021, briefly serving as a Senior Software Development Engineer. His responsibilities included algorithm development and optimization, particularly in distributed systems.
Education and Expertise
Bennet Huber studied Computer Science and Mathematics at Penn State University, earning a Bachelor of Science degree from 2006 to 2010. He also attended Lower Merion High School from 2001 to 2005. His academic background supports his expertise in microservice architectures and programming languages, with a focus on solving problems related to highly scalable systems and high-performance computing.
Internship Experience
Bennet Huber gained early industry experience through internships. He interned at Temple Allen Industries in 2006 for six months and at Cisco Systems in 2007 and 2008 for two months each. These roles provided foundational skills in software development and engineering practices.
Specialized Knowledge
Bennet Huber possesses specialized knowledge in Datapath, a proprietary Amazon relational programming language. His expertise extends to backend cloud architecture and algorithm optimization, particularly in the context of natural language processing applications, demonstrating his capability in high-performance computing.