Principal Software Engineer - Confluence AI
- Canada, United States
- Remote
- Posted Oct 15, 2026
- 1 position
US$174,051–US$273,775 / year
Opens an external site
- Experience level
- Lead · 10+ years
- Apply by
- Oct 15, 2027
- Posting language
- English
- Working hours
- 40 hours per week
Job summary
Lead the technical strategy and development of high-quality AI experiences within the Confluence platform. Collaborate with cross-functional teams to integrate generative AI, improve product adoption, and ensure scalable, reliable system performance.
Job details
Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Responsibilities As a Principal Software Engineer in the Confluence AI group, you will lead the development of high-quality AI experiences that help teams create, discover, and collaborate on knowledge. You will shape technical strategy across the full stack, applying advances in AI to improve product quality, deepen user trust, and drive sustained adoption and growth. Working closely with product, design, engineering, analytics, and machine learning teams, you will turn emerging technologies into reliable, intuitive capabilities that deliver lasting customer value. Technical Leadership & Execution Drive complex technical decisions that shape the direction of Confluence AI across teams and multiple quarters Lead the largest and most complex initiatives from architecture and prototyping through launch and iteration Set technical direction across user experiences, backend services, and AI integrations, balancing delivery speed, quality, and long-term maintainability Design scalable, resilient systems that meet performance, reliability, security, and cost requirements AI Quality & Innovation Apply advances in generative AI, retrieval, agents, and evaluation to improve the usefulness, accuracy, and consistency of Confluence AI experiences Build quality into the full product lifecycle through automated evaluations, representative test datasets, user feedback, and production monitoring Prototype and assess emerging technologies, adopting approaches that demonstrate measurable improvements in customer outcomes Partner with machine learning and platform teams to improve grounding, context retrieval, orchestration, and safeguards Establish continuous improvement processes that connect production insights to engineering priorities Product Adoption & Sustained Growth Build intuitive full stack experiences that make AI capabilities easy to discover, understand, and incorporate into everyday workflows Partner with product, design, and analytics to identify barriers to adoption and translate insights into targeted improvements Define and track measures of AI quality, activation, repeat usage, retention, and customer value Use experimentation to understand how improvements in quality and usability contribute to sustained growth Prioritize experiences that earn user trust and deliver recurring value across Confluence Cross-Functional Collaboration Collaborate closely with product managers, designers, engineers, and data scientists to deliver cohesive AI experiences Lead initiatives across Confluence and Atlassian, aligning shared capabilities with product needs Communicate technical strategy, tradeoffs, and results clearly to technical and non-technical stakeholders Bridge gaps across frontend, backend, AI infrastructure, and analytics to ensure end-to-end ownership of customer outcomes Mentorship & Organizational Impact Mentor engineers across levels, strengthening full stack engineering, AI integration, and experimentation practices Raise engineering standards through technical guidance, design reviews, and hands-on contributions Develop reusable capabilities and practices that help teams deliver high-quality AI experiences more effectively Share learning across the organization and build a culture of curiosity, accountability, and continuous improvement Decision Making & Direction Make informed decisions by balancing customer impact, technical feasibility, delivery speed, risk, and cost Reduce ambiguity through focused prototypes, experiments, and measurable success criteria Connect individual capabilities to a coherent Confluence AI strategy and broader Atlassian platform direction Anticipate evolving customer needs and technology shifts, guiding investments that support durable product quality and growth Compensation 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. Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. This role may also be eligible for benefits, bonuses, commissions, and equity. Pay Ranges In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are: Zone A: $209,700 - $273,775 Zone B: $188,730 - $246,398 Zone C: $174,051 - $227,233 In Canada, for this role, our current base pay range for new hires is: Canada: CA$172,800 - CA$225,600 Qualifications Benefits & Perks 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 go.atlassian.com/perksandbenefits. About 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. To learn more about our culture and hiring process, visit go.atlassian.com/crh. In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
What you’ll do
Lead the technical strategy and development of high-quality AI experiences within the Confluence platform. Collaborate with cross-functional teams to integrate generative AI, improve product adoption, and ensure scalable, reliable system performance.
Requirements
The role requires extensive experience in full-stack engineering and technical leadership, particularly in AI and machine learning integration. Candidates must demonstrate the ability to drive complex technical initiatives and mentor engineering teams across multiple levels.
Benefits
- Health and wellbeing resources
- Paid volunteer days
- Equity
- Bonuses
- Commissions
Listed skills
- Mentorship · Preferred
- Machine learning · Preferred
- Stakeholder Management · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Software engineering
- Artificial intelligence
- Generative AI
- Technical leadership
- System architecture
- Full stack development
- Machine learning
- Data analytics
- Product strategy
- Mentorship
- Experimentation
- Retrieval augmented generation
- Cloud infrastructure
- Performance optimization
- Security
- Stakeholder management
- Scalability Design
- Technical Strategy
- Cross-Functional Collaboration
- Test Datasets
- Atlassian Confluence
- Full Stack Development
- Product Adoption Strategies
- Generative Artificial Intelligence
- Accountability
- Workflow Management
- Curiosity
- Emerging Technologies
- Resilience
- Technical Leadership
- AI Integrations
- Automation
- Decision Making
- Continuous Improvement Process
- Equities
- Front End Design
- Innovation
- Product Lifecycle Management
- Machine Learning
- Maintainability
- Product Design
- Prototyping
- Software Engineering
- Usability
- Product Quality (QA/QC)
- Balancing (Ledger/Billing)
- Reliability
- Teamwork
- User Feedback
- Artificial Intelligence Strategy
Job areas
- Software
- Technology
- Engineering
- Data & Analytics
- Management & Leadership
- Principal Software Engineer
- Software Developer / Engineer
- Software Developers
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