Nir Shney Dor
About Nir Shney Dor
Nir Shney Dor is the Director of Solutions Architecture & AI/ML at AUTOMAT-IT in Israel, where he has worked since 2023. With over 18 years of experience in leading R&D and engineering teams, he has held various leadership roles in notable companies including Amazon Web Services and Jelly Button.
Current Role at Automat
Nir Shney Dor serves as the Director of Solutions Architecture & AI/ML at AUTOMAT-IT since 2023. In this role, he focuses on developing and implementing advanced solutions in artificial intelligence and machine learning. His leadership in this position reflects his commitment to driving innovation and results within the organization.
Professional Experience
Nir Shney Dor has over 18 years of experience in technology and engineering roles. His career includes positions such as Senior Solutions Architect at Amazon Web Services (AWS) from 2019 to 2021, where he specialized in AI/ML solutions. He also held leadership roles at Jelly Button, including R&D Director and Director of Technology, contributing to the company's technological advancements.
Education and Expertise
Nir Shney Dor holds a Bachelor of Arts in Computer Science from The Academic College of Tel-Aviv, Yaffo, completed between 2001 and 2004. He furthered his education with a Master of Business Administration (MBA) in Management and Organizational Behavior from Bar Ilan University, earned from 2012 to 2014. His educational background supports his extensive expertise in technology and management.
Leadership Philosophy
Nir believes in thinking big and driving results as a team, which reflects his leadership philosophy. This approach has guided his management style throughout his career, particularly in leading multidisciplinary R&D and engineering teams across various organizations.
Certifications and Skills
Nir Shney Dor holds six AWS certifications, demonstrating his proficiency in Amazon Web Services technologies. His skills encompass areas such as Business Intelligence (BI), Quality Assurance (QA), and DevOps, along with hands-on experience in defining architecture for complex solutions in high-scale software development and machine learning.