Software Engineer II

Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. This role can be based remotely or from an Atlassian office where eligible. Whatever your preference - working from home, an office, or in between - you can choose the place that's best for your work and your lifestyle. We call this TEAM anywhere . Your future team Kairos is part of Atlassian’s Jira Service Management AI mission, focused on building intelligent service experiences that help customers resolve requests faster and with less manual effort. The team contributes to Request Resolver and related AI-powered service workflows, where backend systems, orchestration, operational reliability, and machine learning-enabled capabilities come together to power customer-facing experiences. Kairos operates in a high-impact space with strong product and engineering complexity. The team works across backend platforms, service integrations, AI-assisted and agentic workflows, and production readiness concerns needed to deliver reliable experiences at scale. This includes solving problems in distributed systems, service quality, observability, execution safety, and applying ML-powered or AI-enabled capabilities in ways that create measurable customer value. We are looking for someone who has already delivered evidence of impact at scale, not just prototypes or experimentation in isolation. Design, build, and ship backend services and platform capabilities that support AI-powered service experiences in Jira Service Management. Contribute to machine learning-enabled product capabilities by productionizing models, signals, ranking, decisioning, or evaluation flows in close partnership with ML, data, and product counterparts. Own complex tasks and scoped projects end-to-end, from technical design through rollout, validation, and post-launch improvements. Write high-quality, well-structured, maintainable code that is adaptable to changing product and platform requirements. Improve the reliability, observability, performance, and operational readiness of the services and features you build. Use data, experiments, and production signals to evaluate the impact of delivered capabilities and inform engineering decisions. Participate in code reviews and contribute to raising the engineering standard within the team. Collaborate across functions to translate ambiguous customer and business problems into scalable backend and ML-supported solutions. Contribute to team productivity through better documentation, clearer technical patterns, and improvements to the codebase that make future work easier. Navigate ambiguity in an AI-first product space and help unblock delivery with thoughtful, pragmatic decisions. 4+ years of experience building backend applications or platforms in production environments Bachelor’s or Master’s degree in Computer Science, Machine Learning, Software Engineering, or a related field, or equivalent practical experience Strong programming skills in one or more modern languages such as Java, Kotlin, Python, Go, or Scala Experience designing and operating scalable distributed systems, microservices, APIs, and event-driven or asynchronous architectures. Hands-on experience delivering machine learning, AI, or data-powered capabilities into production software, not only experimentation environments Experience working with data pipelines, feature or signal integration, model-serving patterns, evaluation frameworks, or production inference workflows. Working knowledge of databases and storage systems, including relational and/or NoSQL technologies Familiarity with cloud platforms and the engineering practices required to build secure, observable, and reliable services at scale Ability to use metrics and evidence to reason about quality, perfor