Why Kaseya? 

Join a fast-growing company transforming the IT management and cybersecurity industry. At Kaseya, we are modernizing how software is designed, built, tested, and operated—combining strong engineering fundamentals with AI-native development practices. 

As a Senior Staff Engineer, you will have the opportunity to shape not only our technology architecture, but also how engineering teams leverage AI to build high-quality software faster and more effectively. 

Join the Kaseya growth rocket ship and see how we are #ChangingLives! 

Job Summary 

We’re hiring a Software Engineer I to provide hands-on technical leadership across our SaaS platforms and shared backend services. 

This role is for an engineer who combines deep expertise in Java, distributed systems, cloud architecture, and software design with a modern, AI-native approach to software engineering. 

You will lead complex initiatives across multiple teams, influence architecture and engineering standards, and remain deeply involved in implementation. You will also help define how engineering teams effectively use AI coding tools, including Claude Code, throughout the software development lifecycle—from understanding existing systems and designing solutions to implementation, testing, debugging, code review, documentation, and modernization. 

This is not a purely architectural role. We are looking for a technical leader who designs, codes, prototypes, reviews, mentors, and leads by example. 

Roles & Responsibilities 

• Define and drive architecture for Java-based platform services, distributed systems, APIs, and event-driven applications across multiple product areas 

• Lead complex technical initiatives spanning multiple engineering teams, services, and business domains 

• Remain highly hands-on through architecture, prototyping, implementation of critical components, code reviews, debugging, and production troubleshooting 

• Champion AI-native software engineering practices, using AI coding tools such as Claude Code to improve developer productivity, code quality, testing, debugging, documentation, and system understanding 

• Establish effective patterns and guardrails for using AI-generated code in production engineering environments 

• Help engineering teams evolve from traditional development workflows toward AI-assisted and agentic software development 

• Identify opportunities where AI can accelerate modernization of legacy systems, test creation, refactoring, migration, and technical debt reduction 

• Partner with Product, Engineering, Security, and Architecture leaders to translate business priorities into scalable technical solutions 

• Guide the evolution of cloud-native architectures, microservices, data flows, integrations, and shared platform capabilities 

• Drive improvements in system performance, availability, observability, security, and operational readiness 

• Establish engineering standards and reusable patterns for Java development, API design, testing, CI/CD, AI-assisted development, and production operations 

• Mentor Senior and Staff Engineers through architecture reviews, technical guidance, hands-on collaboration, and modern AI-enabled engineering practices 

• Evaluate emerging engineering and AI technologies and determine where they can meaningfully improve our products and engineering organization 

Required Qualifications 

• 2+ years of software engineering experience building production SaaS applications, distributed systems, or enterprise software platforms 

• 1+ years of experience developing production backend services using Java 

• Strong hands-on coding skills and the ability to design, implement, review, debug, and operate complex production software 

• Proven experience providing technical leadership across multiple engineering teams or product areas 

• Experience designing and operating distributed systems on AWS, Azure, or GCP 

• Experience leading architecture reviews and establishing engineering standards or practices adopted across multiple teams 

• Demonstrated experience using AI-assisted coding tools as part of real software engineering workflows 

• Ability to use AI effectively for code generation, codebase exploration, refactoring, testing, debugging, documentation, and technical problem-solving 

• Strong understanding of software engineering fundamentals and the ability to critically review, validate, test, and improve AI-generated code 

• Ability to mentor engineers and influence technical direction without relying solely on organizational authority 

Preferred Qualifications 

• Hands-on experience with Claude Code or similar agentic AI coding tools 

• Experience with Java technologies such as Spring Boot, Spring Cloud, Hibernate, Kafka, or similar frameworks 

• Experience designing cloud-native, microservices-based, or event-driven architectures 

• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle 

• Experience leading platform modernization, cloud migration, or large-scale re-architecture initiatives 

• Experience using AI to accelerate modernization of large or legacy codebases 

• Experience improving reliability, observability, performance, testing, or operational practices across production systems 

• Experience integrating AI-enabled capabilities, LLMs, agents, or AI services into production software 

• Experience developing engineering standards, workflows, or guardrails for AI-assisted software development 

• Familiarity with modern AI engineering concepts such as LLM APIs, tool use, agents, RAG, evaluation, and prompt/context engineering 

• Experience measuring and improving engineering productivity using AI-enabled development workflows 

What Success Looks Like 

A successful Senior Staff Engineer at Kaseya does more than design systems. You will: 

• Build: Stay close to the code and deliver critical technical solutions. 

• Lead: Set technical direction and drive complex initiatives across teams. 

• Modernize: Improve architecture, engineering practices, and legacy systems. 

• Amplify: Use AI to increase the effectiveness and velocity of engineering teams. 

• Mentor: Raise the technical capabilities of engineers around you. 

• Own: Take responsibility for solutions from architecture and implementation through production operation. 

We are looking for engineers who see AI not as a replacement for engineering fundamentals, but as a powerful multiplier for exceptional engineers.