Sales | San Francisco, United States | Remote, Remote | Full-Time
What you'll doWe're hiring a Customer Success Architect (AI-SDLC) to help enterprise customers put AI to work across the software development lifecycle, from planning and knowledge discovery to development, review, testing, and release. This individual contributor role sits within our Customer Success Architect team and reports to a regional leader.
In this role, you'll lead time-boxed technical engagements and build solutions alongside customers, connecting Atlassian workflows with enterprise knowledge and the development tools their teams use. The work combines technical depth, customer-facing consulting, and software delivery expertise. Working with engineering and platform teams, you'll identify high-impact opportunities, validate working solutions, and establish measurable improvements in adoption, developer experience, and software delivery.
You'll also partner with Account Teams, Customer Success, and Product teams to bring customers' planning, knowledge, and development workflows together. You'll help engineering teams move beyond isolated AI experiments and turn their investments into practical, repeatable ways of working, with connected workflows and clear governance. As customers achieve results, you'll help them share what worked and what they learned with their peers.
As a senior individual contributor, you'll contribute customer insight, practical patterns, and field feedback that help Atlassian improve how its software delivery products are adopted across enterprise customers. You will also serve as a mentor for your teammates, sharing your learnings leveraging your experience to upskill the entire team.
On your first day, we'll expect you to have:- Discovery: Assess how customers deliver software, the development tools they use, and their readiness to adopt AI. Partner with engineering, platform, and developer experience teams to find bottlenecks, gaps in context, and repetitive work across planning, development, review, testing, and release. Help customers prioritize AI use cases with clear adoption goals and measurable delivery outcomes.
- Design: Work with customers to design AI-enabled workflows that connect requirements, team knowledge, and development tools. Help shape practical use cases such as development readiness, knowledge discovery, implementation planning, and review preparation. For each workflow, define the integrations and context sources it requires, where human review fits, and how to assess its success.
- Deploy: Guide customers through time-boxed pilots and technical activation, working alongside their teams to validate workflows in their environment. Measure adoption, output quality, and delivery impact against agreed baselines. Give customers the guidance and ongoing feedback processes they need to maintain, refine, and scale successful practices independently.
- Collaborate: Build coordinated technical activation plans with Account Teams, CSMs, and relevant product specialists. Partner with customer engineering, platform, security, and AI stakeholders to bring AI-enabled practices into their existing toolchains and ways of working. Help address the adoption barriers and technical dependencies involved.
- Advocate: Share insights from customer feedback, adoption patterns, and technical friction that relevant Atlassian product and engineering teams can act on. Document validated use cases, reusable patterns, and customer outcomes to improve future engagements and help scale AI-SDLC adoption.
- Travel up to 15% domestically and internationally for customer and internal meetings.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience.This role may also be eligible for benefits, bonuses, commissions, and equity.
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