60 Atlassian Full Stack Software Engineer Jobs Hiring Near You

Atlassians have the flexibility to work where they can collaborate most effectively with their team, whether at home, one of our global offices, or both. We hire in any country where we have a legal entity. Learn how we work at go.atlassian.com/distributed.

Atlassian’s Grad++ program combines hands-on technical training, professional growth opportunities, dedicated mentorship, and strong social connections. This holistic approach empowers students to hit the ground running and sets them up for a successful and impactful career at Atlassian!

This role is located in Burnaby, Richmond or Vancouver, British Columbia. You must be willing and able to work out of one of these locations to qualify.

This position is not eligible for employer sponsorship for work authorization at the time of hire. Applicants who may require employer sponsorship in the future are encouraged to indicate this during the application process.

Build Production-Ready Features: Develop scalable code for Atlassian's products (Jira, Confluence, Trello) used by millions of teams worldwide, contributing to reliable systems that power global collaboration

Own End-to-End Projects: Take ownership of features from design through deployment, including implementation, testing, and monitoring in production environments

Collaborate in Agile Teams: Work closely with senior engineers, product managers, and designers using Agile methodologies and lean practices to deliver impactful solutions

Innovate with AI/ML Technologies: Contribute to AI-powered features and integrations, working with modern frameworks, agentic systems, and intelligent automation capabilities

Solve Complex Technical Problems: Tackle challenging issues related to distributed systems, data processing, and user experience optimization while using data-driven insights to validate assumptions and improve products.

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.

This role may also be eligible for benefits, bonuses, commissions, and equity.

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit Atlassian Internships: Students and New Grads | Atlassian.

At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

Canada: CA$94,500 - CA$123,375

Currently enrolled full time in aBachelors or Masters degree program in Computer Science, Software Engineering or related technical field and are graduating by August 2027.

Experience with Python, Java, or other modern object oriented languages, with exposure to AI/ML frameworks (TensorFlow, PyTorch, scikit-learn) and understanding of machine learning fundamentals

Proven development skills through internships, work experience, projects, or publications, including experience with APIs, cloud platforms, or AI-powered applications

Strong understanding of data structures, algorithms, statistical concepts, and familiarity with design patterns for modern systems including AI/ML architectural patterns (data pipelines, model serving, microservices)

Exposure to agentic AI systems, autonomous agents, modern AI protocols (MCP, function calling), and AI-assisted development approaches.

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