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Kaseya is seeking a Senior Staff Software Engineer to lead the architecture and evolution of Java-based SaaS platforms and shared backend services. This is a hands-on technical leadership role focused on solving complex distributed systems challenges, leading initiatives across multiple teams, and improving the scalability, reliability, and maintainability of business-critical applications.
You will define and drive architecture for Java-based platform services, distributed systems, APIs, and event-driven applications across multiple product areas. The role involves leading complex technical initiatives spanning multiple engineering teams and business domains while remaining deeply involved in technical prototyping, implementation of critical components, code reviews, and production troubleshooting.
Key responsibilities include partnering with Product, Engineering, Security, and Architecture leaders to translate business priorities into scalable technical solutions; guiding the evolution of cloud-native architectures, microservices, data flows, and shared platform capabilities; driving improvements in system performance, availability, observability, security, and operational readiness; establishing engineering standards and reusable patterns for Java development, API design, testing, CI/CD, and production operations; and mentoring Senior and Staff Engineers through architecture reviews and technical guidance.
Required qualifications: 10+ years of software engineering experience building production SaaS applications, distributed systems, or enterprise software platforms; 6+ years developing production backend services using Java; experience leading architecture and delivery of technical initiatives spanning multiple teams; experience designing and operating distributed systems on AWS, Azure, or GCP; and experience leading architecture reviews and introducing technical standards adopted across multiple teams.
Preferred qualifications include experience with Spring Boot, Spring Cloud, Hibernate, Kafka, cloud-native and microservices architectures, relational databases (PostgreSQL, MySQL, SQL Server, Oracle), platform modernization and cloud migration initiatives, improving reliability and observability across production systems, and integrating AI-enabled capabilities into production software.
