Engineering | Seattle, United States | Remote, Remote | Canada, Canada | San Francisco, United States | Mountain View, United States or Remote
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As a Senior Software Engineer in the Confluence AI group, you will build high-quality AI experiences that help teams create, discover, and collaborate on knowledge. You will work across the full stack, applying advances in AI to improve product quality, deepen user trust, and drive sustained adoption and growth. Partnering with product, design, analytics, and machine learning teams, you will turn emerging technologies into reliable, intuitive features that deliver lasting customer value.
Technical Ownership & Execution- Own complex features from technical design and implementation through launch and ongoing improvement
- Build cohesive experiences across frontend interfaces, backend services, and AI integrations
- Contribute to architecture decisions, balancing delivery speed, quality, and long-term maintainability
- Deliver scalable, reliable software that meets performance, security, accessibility, 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 features
- Develop automated evaluations and representative test datasets to validate quality and prevent regressions
- Prototype and evaluate emerging technologies against concrete customer needs and measurable outcomes
- Collaborate with machine learning and platform engineers to improve grounding, context retrieval, orchestration, and safeguards
- Use production monitoring and user feedback to diagnose issues and continuously improve AI experiences
Product Adoption & Sustained Growth- Build intuitive experiences that make AI features easy to discover, understand, and use in everyday workflows
- Work with product, design, and analytics to identify and address barriers to adoption
- Instrument features to measure AI quality, activation, repeat usage, retention, and customer value
- Design and run experiments to assess how quality and usability improvements affect adoption and engagement
- Iterate on features to earn user trust and deliver recurring value
Cross-Functional Collaboration- Partner with product managers, designers, engineers, and data scientists to translate customer needs into practical technical solutions
- Coordinate with adjacent teams to integrate shared AI capabilities and resolve dependencies
- Communicate technical decisions, tradeoffs, and experiment results clearly
- Contribute across frontend, backend, and AI integration boundaries to deliver complete customer experiences
Mentorship & Team Impact- Mentor engineers through pairing, code reviews, and technical guidance
- Improve team practices for testing, AI evaluation, observability, and software delivery
- Build reusable components and share approaches that help the team deliver more effectively
- Contribute to a culture of curiosity, collaboration, accountability, and continuous learning
Problem Solving & Decision Making- Independently break down ambiguous problems into achievable implementation plans
- Use prototypes, experiments, and data to reduce uncertainty and guide decisions
- Balance customer impact, technical complexity, risk, and cost when choosing solutions
- Identify opportunities for improvement and work with technical leaders to align them with the broader Confluence AI direction
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.
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