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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.

Atlassian's mission is to unleash the potential of every team, with collaboration products like Jira, Confluence, and Bitbucket that power teamwork and help teams succeed worldwide. The role is in the Central AI Org, specifically the AI & ML Platform team, which drives AI innovation across Atlassian products and aims to deliver seamless AI experiences and a robust AI infrastructure, including a centralized search, Q&A, and conversational AI system. The AI & ML Platform Team seeks to democratize AI and ML by building horizontal capabilities and integrating with the Atlassian Data Platform so teams can develop, deploy, measure, and operate AI/ML experiences securely. As a Senior Machine Learning System Engineer, you'll develop core infrastructure enabling engineers and data scientists to build, train, evaluate, deploy, and manage ML models and pipelines, collaborating with product teams like Jira and Confluence and tackling datasets and LLM fine-tuning. You will lead projects from design to launch and deliver solutions used across Atlassian, perform code reviews and documentation, collaborate on company-wide initiatives, and mentor junior team members.

Atlassian offers flexible work options—office, remote, or hybrid—and hires globally wherever they have a legal entity to support employees' family and personal priorities. They are seeking a Senior Machine Learning Engineer to join the AI Context team within the broader Rovo + AI organization to build agentic LLM harnesses powering high-visibility Rovo AI features and context-aware experiences for users and AI agents. The AI Context team operates across Sydney, Melbourne, Brisbane, and the US West Coast, bringing together software engineers and ML engineers who work with Rovo + AI and product teams to deliver insights, modeling, and personalization. Responsibilities include designing, building, shipping, and operating agentic LLM harness solutions, improving production LLM quality and cost, developing evaluation capabilities, and contributing to fine-tuning and model serving while shaping long-term technical direction. The role involves navigating complex systems, proposing durable architectures, influencing technical direction across stakeholders, leading small virtual squads, coaching junior engineers, and acting as a thought partner to Engineering Managers and Heads of Engineering to help achieve key results.