Chris De Lorenzo
About Chris De Lorenzo
Chris De Lorenzo is a Regional Sales Manager at CAST AI, with extensive experience in sales and management roles at various technology companies, including Datadog and LogMeIn. He holds a Bachelor of Science in Business Administration from Saint Michael's College and specializes in AI-driven cloud optimization.
Current Role at CAST AI
Chris De Lorenzo serves as the Regional Sales Manager at CAST AI, a position he has held since 2024. In this role, he focuses on driving sales initiatives and expanding the company's market presence in the Greater Boston area. His expertise in AI-driven cloud optimization and Kubernetes automation supports CAST AI's mission to enhance cloud resource utilization.
Previous Experience at Datadog
Prior to his current role, Chris De Lorenzo worked at Datadog in various capacities from 2015 to 2020. He began as an Account Executive and progressed to Manager of Sales Development, Senior Team Lead, and finally Commercial Sales Manager. His tenure at Datadog equipped him with significant experience in sales strategies and team leadership within the tech industry.
Career Background in Sales and Management
Chris De Lorenzo has a diverse background in sales and management across multiple organizations. He held positions at LogMeIn as an Account Manager and in SaaS sales, and at Starburst as an Account Executive and Director of Inside Sales. Additionally, he worked as a Regional Sales Manager at Observe, Inc. His career reflects a strong focus on sales performance and team development.
Educational Background
Chris De Lorenzo earned a Bachelor of Science degree in Business Administration from Saint Michael's College, where he studied from 2006 to 2010. His foundational education has contributed to his understanding of business operations and sales management, which he has applied throughout his career.
Expertise in AI-Driven Cloud Optimization
Chris De Lorenzo possesses expertise in AI-driven cloud optimization, particularly in the areas of Kubernetes automation, optimization, security, and cost management. He utilizes advanced machine learning algorithms to enhance cloud resource utilization, aiming to significantly reduce cloud expenditures.