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The Rovo Mobile team is seeking an experienced principal mobile developer with React Native expertise to help build the AI vision on mobile devices and maintain the Rovo app at Atlassian. You will collaborate with design to develop new features and workflows, verify their impact and usability, and be responsible for feature development and regular app releases. The role emphasizes customer focus, building high-quality features and infrastructure that are fast, testable, and scalable, and driving collaboration with engineers, designers, and managers to address user pain points. You will contribute to code reviews and documentation, tackle complex bug fixes, and lead projects from technical design and implementation through launch to operation. You will also onboard and mentor junior engineers.

Atlassian is hiring a Principal Security Engineer focused on AI/ML to protect models, data pipelines, and inference services with innovative defences and governance, with eligibility open to candidates in Australia and New Zealand due to sufficient time zone overlap. The role involves leading security for AI platforms and product experiences, partnering across engineering, platform, infrastructure, and privacy to foster a culture of secure and trustworthy AI that meets high industry standards. The Principal Product Security Engineer will act as the technical SME, promoting automation, reviewing designs, and driving security teams to equip engineering partner teams with the latest tools, techniques, and methodologies to enhance AI security. On day one, candidates should have hands-on experience securing AI/ML systems, cloud security architecture for AI/ML workloads, coding in Java, JavaScript, Python, or Go (and at least one scripting language), and experience leading large-scale projects with SME guidance to stakeholders. Desirable extras include security-focused roles, application security for ML/LLM services, mentoring, CVEs, open-source contributions, and delivered industry presentations.

Atlassian lets employees choose where to work—office, home, or a mix—and hires in any country where it has a legal entity. Its mission is to unleash the potential of every team, with products like Jira, Confluence, and Bitbucket that support collaboration across diverse teams. The Central AI Org drives AI innovation across Atlassian, building horizontal AI capabilities, a centralized Search/Q&A/Conversational AI system, and exploring external AI integrations. The AI & ML Platform Team aims to democratize AI/ML by developing tools to build, deploy, and operate AI experiences, integrating with the Atlassian Data Platform while enforcing security and data usage policies. As a Senior Machine Learning System Engineer, you would help create the core infrastructure for ML models and pipelines, collaborate with Jira and Confluence teams, curate datasets and fine-tune LLMs, lead projects from design to launch, and mentor junior engineers while driving cross-team initiatives.

Atlassian supports flexible work arrangements—office, remote, or hybrid—and hires in any country where it has a legal entity. As a Senior ML System Engineer on the AI & ML Platform, you’ll build and refine the core infrastructure that enables Atlassian engineers, ML engineers, and data scientists to create, train, evaluate, deploy, and manage ML models and pipelines, collaborating with product teams like Jira and Confluence. Responsibilities include curating high-quality ML datasets, fine-tuning open-source or proprietary LLMs, solving complex infrastructure and architectural challenges, leading projects from design to launch, and delivering code reviews, documentation, bug fixes, and mentoring junior teammates. The role requires 5+ years of experience in building ML/AI infrastructure, comprehensive ML lifecycle expertise, large-scale distributed system design, and MLOps/automation, with the ability to partner across engineering teams on company-wide initiatives. Preferred qualifications include expert Python and ML framework proficiency (PyTorch, TensorFlow, or JAX), familiarity with Go/Java/Scala, hands-on cloud experience (AWS, GCP, or Azure) and AI services, big data tooling (Spark, Ray, or Dask), performance optimization, and experience with generative AI systems and retrieval-augmented generation.

The role is a Cloud Network Engineer on Atlassian's Edge Networking team, responsible for scaling cloud networking services to provide a reliable network experience for global users of Jira, Confluence, Trello, and Bitbucket. The ideal candidate is a technical leader who stays current with networking, proxies, and reliability trends, thrives in teams balancing operational and project work, and enjoys sharing knowledge. They should bring deep expertise in modern cloud networking infrastructure, programming, and operational experience, with a drive to change the status quo to improve reliability, performance, scalability, and cost efficiency. Responsibilities include writing code to automate and operate large proxy fleets across globally distributed regions, responding to operational events, contributing to major projects delivering new networking features, designing new network features, investigating security, reliability, and cost improvements, and mentoring/hiring. Atlassian supports flexible work arrangements (office, home, or hybrid) and can hire in any country with a legal entity, with the role reporting to the Senior Engineering Manager of Edge Networking.

Atlassian supports flexible work locations and hires globally, with the Future Team Search Platform delivering fast, reliable search across all Atlassian products through scalable, low-latency infrastructure. The Principal Machine Learning Systems Engineer role combines search, machine learning, and experimentation, requiring about 70% engineering and 30% ML to deliver ML-powered solutions that affect millions of users. Responsibilities include solving large-scale technical design problems, building ranking models, feature engineering for offline and online inference, and architecting data infrastructure for high-velocity search and experimentation data, plus end-to-end production deployment with monitoring. The role also entails leading code reviews, documentation, mentoring junior engineers, partnering across teams on company-wide programs, and communicating complex concepts to stakeholders. Required background includes 10+ years of software leadership, experience with ML workflows at scale, a track record of launching AI/ML products, a CS degree, proficiency in languages like Java or Python, cloud experience, with desirable experience in OpenSearch/Elasticsearch, developer productivity, experimentation, CI/CD, and 2+ years running search systems at scale.

At Atlassian, employees can choose their work environment, whether in an office or remotely, allowing greater flexibility in balancing personal and family needs. The company hires globally, including establishing legal entities in various countries. Senior Support Engineers are vital in providing advanced support for enterprise customers, particularly those transitioning from on-premise products to Atlassian Cloud. They troubleshoot technical issues, offer assistance through various channels, and handle escalations, leveraging their expertise and collaboration skills. Additionally, these engineers are expected to identify trends for improvement, advocate for customer needs, contribute to documentation, and occasionally work during weekends, all while supporting Japanese-speaking customers.

Atlassian offers flexible work arrangements, allowing employees to choose between office work, remote work, or a hybrid model to better manage personal responsibilities. They are actively hiring Senior Support Engineers globally, focusing on providing advanced support to enterprise clients transitioning from on-premise Atlassian products to the Atlassian Cloud. These engineers enhance customer experiences through effective troubleshooting, technical support via various channels, and handling escalations using their expertise. Responsibilities also include performing case reviews to identify trends for improvement, advocating customer needs for feature enhancements, and creating documentation for support teams. The role requires proficiency in both Japanese and English, along with occasional weekend shifts, as engineers engage with diverse teams and contribute to customer migration projects.