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Atlassian's mission is to unleash the potential of every team, with products like Jira, Confluence, and Bitbucket that support collaboration across diverse teams and processes, even powering milestones such as NASA's Mars rover and Cochlear's hearing solutions. The Central AI Org is dedicated to driving AI innovation across all Atlassian products and platforms, delivering seamless AI experiences and building a robust Atlassian AI infrastructure, including a centralized Search, Q&A, and Conversational AI system that integrates with all Atlassian products and exploring AI solutions beyond the Atlassian ecosystem. The AI & ML Platform Team aims to democratize AI/ML for Atlassian’s teams, customers, and ecosystem by building productive, reliable tools for developing, deploying, measuring, and operating AI/ML experiences, with tight integration to the Atlassian Data Platform and strict security and data-usage policies. Atlassian offers flexible work options (office, remote, or hybrid) and hires in any country where it has a legal entity. In the Senior Machine Learning System Engineer role, you will develop and refine the core infrastructure that enables engineers and data scientists to build, train, evaluate, deploy, and manage ML models and pipelines, collaborate with product teams like Jira and Confluence to solve ML challenges, curate high-quality datasets and fine-tune LLMs, lead projects from design to launch, deliver solutions used by millions, perform code reviews and documentation, and mentor junior engineers.

Atlassian offers flexible work locations—office, remote, or hybrid—and hires in any country where it has a legal entity. They are seeking a Senior Machine Learning Engineer to join the AI Context team within Rovo + AI, building agentic LLM harnesses for high-visibility Rovo AI features and context-aware experiences for users and agents. The AI Context team spans Sydney, Melbourne, Brisbane, and the US West Coast, comprising software engineers and ML engineers who collaborate with Rovo + AI and product teams to deliver contextual insights and personalization. In this role you will design, build, ship, and operate agentic LLM harness solutions, improve quality and reduce cost of production LLM systems, and contribute to evaluation, fine-tuning, and model serving while defining long-term technical direction. You will navigate complex systems, lead small virtual squads, act as a thought partner to Engineering Managers, influence technical direction across stakeholders, and coach junior engineers to help the team achieve key results.

The Enterprise Security Engineer at Atlassian is a hands-on role responsible for implementing, operating, and improving security controls across identity, endpoints, cloud, SaaS, data, and workforce technologies, turning security strategy into practical, secure-by-default controls that don’t slow the business. They partner with Enterprise IT, Corporate Engineering, SRE/Platform teams, Legal, Privacy, Product Security, and other stakeholders, participate in Atlassian’s Customer Zero initiative, and are based in Australia/New Zealand. Key duties include designing and maintaining security controls across identity, access, cloud (AWS/GCP), SaaS, and data-protection domains; remediating gaps; enabling secure baselines; conducting security reviews for new tools and workflows; and supporting cyber-related physical security integrations. The role also covers identity lifecycle, privileged access, authentication/authorization, insider risk monitoring, cloud and endpoint protection, DLP and data classification, automation, IaC/CI-CD security checks, on-call rotations and post-incident reviews, and SaaS supply chain/vendor risk assessments. Success is measured by timely delivery of tasks and deployments, reduction of security escalations, development of reliable automation, closure of posture gaps, and effective cross-functional collaboration and continuous learning.

The Enterprise Security Engineer is a hands-on role responsible for implementing, operating, and improving security controls across corporate architecture, cloud services, endpoints, identity, data, and workforce technologies, translating strategy into practical, secure-by-default measures. They collaborate with Enterprise IT, Corporate Engineering, SRE and Platform teams, Business Systems, Product Security, Legal, Privacy, and other stakeholders, and participate in Atlassian’s Customer Zero initiative to validate capabilities internally before broader adoption, based in Australia/New Zealand. The role designs, implements, operates, and maintains security controls across identity, endpoints, network, cloud (AWS/GCP), SaaS, and data protection, remediating gaps and rolling out secure baseline configurations and paved-path implementations. It includes strengthening identity and access governance, monitoring insider risk, securing service accounts and bot credentials, and implementing guardrails, DLP, and data-classification across cloud, SaaS, and endpoint environments, while contributing to security reviews for new tools. You’ll also build automation and infrastructure-as-code security checks, participate in on-call rotations and post-incident reviews, and assess SaaS supply chain and third-party risk, with success measured by timely delivery, reduced toil, improved security hygiene, and effective cross-functional collaboration.