Principal Software Engineer - Confluence AI

Principal Software Engineer - Confluence AI  Engineering | Canada, Canada | Remote, Remote | San Francisco, United States | Seattle, United States | Mountain View, United States or Remote
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.
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
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…