Principal Software Engineer - Confluence AI

Atlassian Corp
  • Seattle, WA
    4 days ago

    Job Description

    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.

    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

    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.

    Numbers & Facts

    LocationSeattle, WA

    Skills

    • Artificial Intelligence (AI)unmatched
    • Continuous Improvementunmatched
    • Cross-Functionalunmatched
    • Customer Retention/Renewalunmatched
    • Customer/Client Researchunmatched
    • Data Scienceunmatched
    • Data Setsunmatched
    • Emerging Technologyunmatched
    • Establish Prioritiesunmatched
    • Legalunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Product Designunmatched
    • Product Lifecycleunmatched
    • Product Supportunmatched
    • Production Controlunmatched
    • Prototypingunmatched
    • Quality Managementunmatched
    • Quality Metricsunmatched
    • Riskunmatched
    • Software Engineeringunmatched
    • Systems Scalabilityunmatched
    • Technical Deliveryunmatched
    • Technical Leadershipunmatched
    • Technical Strategyunmatched
    • Technical/Engineering Designunmatched
    • Technology Analysisunmatched
    • Testingunmatched
    • Usability Engineeringunmatched
    • User Interface/Experience (UI/UX)unmatched

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