AI-powered IT management and cybersecurity platform for MSPs and SMBs
Kaseya operates a large, multi-product IT infrastructure and security suite (RMM, PSA, backup, SOC) serving over 50,000 managed service providers and small-to-medium businesses globally. The tech stack reveals a Java-first, containerized architecture (Docker, Kubernetes, Spring) deployed across AWS, Azure, and on-premises environments, with active adoption of AWS managed services (ECS, SQS, DynamoDB) and observability tools (Pendo, Whatfix) — signaling a shift toward cloud-native operations and improved user adoption. Platform modernization and cloud spend optimization are documented pain points, underscoring a multi-year infrastructure transition.
Notable leadership hires: Technical Lead, Strategy & Analytics Director, Director Operations Program Management, Engineering Director
Kaseya is a privately held IT management software company founded in 2000, headquartered in Miami, FL, with 5,001–10,000 employees across engineering, sales, support, and operations globally. The platform integrates remote infrastructure management, endpoint security, backup and recovery, and SOC functionality into a unified suite (IT Complete™) designed for MSPs and SMBs. The company operates a sales-and-engineering-led organization: active hiring spans 11 countries, with engineering and sales departments both actively scaling, and notable focus on product leadership roles (director, VP, technical lead) alongside execution-oriented engineering. Current internal initiatives include cross-product adoption strategies, multi-year account expansion, and KPI framework development.
Java, Kotlin, Spring, .NET, and ASP.NET Core for backend services; Docker and Kubernetes for containerization; AWS, Azure, and OCI for cloud infrastructure; SQL and ClickHouse for data; GitHub and Bitbucket for version control; Jenkins and TeamCity for CI/CD.
Active projects include platform modernization, cloud usage analysis, AI/ML integration, and cross-sell/upsell across the IT Complete suite. Pain points center on reducing time-to-value, adoption barriers, cloud spend optimization, and reworking CI/CD and Kubernetes infrastructure.
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