Staff Software Engineer

Overview

Staff Software Engineer to provide hands-on technical leadership across Kaseya's SaaS platforms and shared backend services, combining deep Java, distributed systems, cloud architecture and software design expertise with an AI-native approach to software engineering.

What you'll do

• 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

What you'll need

• 10+ years of software engineering experience building production SaaS applications, distributed systems, or enterprise software platforms
• 6+ 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

Nice to have

• 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

Details

• Location: Pune, India