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Atlassian

HQ
Sydney
Total Offices: 2
11,000 Total Employees
Year Founded: 2012

Atlassian Offices

Atlassian is headquartered in Sydney and has 2 office locations.

Remote Workplace

Employees work remotely.

Atlassians have flexibility in where they work to support their family, personal goals, and other priorities. Our approach to distributed work allows us to tap into talent beyond our office locations, and to reimagine how work gets done.


Global Office Locations

Australia

Australia

Recently posted jobs

2 Hours AgoSaved
In-Office or Remote
3 Locations
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Implements, operates, and improves enterprise security controls across identity, endpoints, cloud, SaaS, networks, and data. Builds automation using scripts, APIs, infrastructure-as-code, and CI/CD security checks. Supports IAM, endpoint protection, DLP, vendor risk assessments, physical access integrations, incident troubleshooting, and security operations. Partners with engineering, IT, legal, privacy, and business teams to deploy secure baselines, remediate risks, monitor control health, and improve enterprise security capabilities.
2 Hours AgoSaved
In-Office or Remote
3 Locations
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Implements and operates enterprise security controls across identity, endpoints, cloud, SaaS, networks, and data. Automates security workflows using scripts, APIs, infrastructure as code, and CI/CD checks. Maintains IAM, endpoint protection, DLP, device posture, and secure configuration baselines. Supports vendor risk reviews, insider-risk monitoring, physical access integrations, incident troubleshooting, on-call operations, documentation, and remediation of security gaps across corporate technology environments.
2 Hours AgoSaved
In-Office or Remote
4 Locations
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Build and improve core AI and machine learning infrastructure enabling teams to develop, train, evaluate, deploy, and operate ML models and pipelines. Design scalable distributed systems, support end-to-end ML lifecycles, implement MLOps automation, collaborate with product engineering teams, lead projects from design through launch, review code, document solutions, and mentor junior engineers. Work may include dataset curation, LLM fine-tuning, model serving, monitoring, and generative AI systems.