Josh brings over a decade of specialized expertise in monitoring and automation technologies to the forefront of AI application oversight. As a Senior Software Engineering Manager at ScienceLogic, he has spent more than seven years architecting and implementing sophisticated monitoring solutions across network, hosting, data center, and managed service provider environments. His deep technical proficiency spans the creation of Dynamic Applications, Runbook Automations, and cloud-native monitoring systems, positioning him uniquely to address the complex challenges of AI application monitoring. Josh's extensive background includes designing high-scale systems capable of handling millions of daily requests and developing custom monitoring solutions for global enterprise customers.

Beyond his technical acumen, Josh exemplifies the collaborative leadership approach essential for successful AI monitoring implementations. His proven track record of building consensus among stakeholders, managing high-performance engineering teams, and translating complex technical concepts into actionable business solutions makes him an invaluable resource for organizations navigating the monitoring landscape of AI applications. With a Computer Science degree from George Mason University and expertise spanning Python development, cloud architectures, and enterprise-scale system design, Josh combines deep technical knowledge with practical management experience to deliver insights that are both technically sound and immediately applicable to real-world AI monitoring challenges.