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Kaseya is a leading provider of AI-powered IT management and cybersecurity software serving Managed Service Providers (MSPs) and internal IT organizations worldwide. The company, founded in 2000 and backed by Insight Partners, manages over 15 million endpoints globally and supports customers in more than 20 countries.
This Senior Staff Software Engineer role provides organization-wide technical leadership for large-scale distributed systems and platform architectures. You will drive long-term scalability, reliability, modernization, and engineering excellence across the company, shaping technical strategy without relying on direct authority.
Key responsibilities include:
- Leading the design and evolution of large-scale distributed systems and platform architectures for scalability and reliability across organizational boundaries
- Defining long-term technical strategy and architecture aligned with business goals
- Driving adoption of AI-assisted development and connecting AI initiatives to measurable engineering and business outcomes
- Identifying high-impact technical opportunities and driving cross-team initiatives spanning multiple systems and domains
- Partnering with engineering, product, and business leadership on technical priorities, roadmaps, and strategic initiatives
- Driving observability, performance, reliability, operational maturity, and systemic risk mitigation across production systems
- Defining technical debt reduction and modernization strategies, including re-platforming roadmaps
- Mentoring senior and staff engineers, establishing high standards for design and operations, and contributing to technical due diligence
Requirements:
- B.S. in Computer Science, Software Engineering, or equivalent practical experience
- 6+ years of software engineering experience driving technical strategy across multiple teams or organizations
- Strong computer science fundamentals including data structures, algorithms, and design patterns
- Deep experience designing large-scale distributed systems or platform architectures with understanding of scalability, reliability, performance, and cost trade-offs
- Hands-on production experience with AWS, GCP, or Azure, including cloud-native services and security best practices
Preferred qualifications:
- Proven ability to operate in ambiguity and drive execution without direct authority
- Deep observability and reliability engineering experience across logging, metrics, tracing, alerting, incident response, and post-mortem improvements
- Experience improving engineering productivity through platforms, tooling, and modern delivery practices
- Forward-looking experience with AI-assisted development and organizational AI strategy
- Full stack/API development experience and proficiency in Rust, C#, or JavaScript; familiarity with OAuth 2.0, OIDC, and SAML
- Strong experience with distributed systems, microservices, Docker, Kubernetes, cloud-native infrastructure, serverless services, and Infrastructure as Code (Terraform, Pulumi, Bicep)
- Experience with secure coding, threat modeling, vulnerability remediation, CI/CD, progressive deployment, relational and non-relational data stores at scale, and technical due diligence
