Customer Success Architect (AI)

What you'll do

In this role, you'll be part of the Technical Customer Success team within the Sales and Success department, focusing on the adoption of Atlassian's AI platform, Rovo. As a Technical CSM (AI), you'll execute time-boxed, co-built technical engagements that take customers from "Rovo is turned on" to real, measurable business value in production. You'll partner directly with enterprise teams to discover high-impact AI use cases, design and build custom Rovo agents, configure third-party connectors, and deploy working solutions into production workflows. Your role bridges deep AI and Atlassian platform expertise with customer success, focusing on measurable adoption outcomes. Your work will involve managing engagements, enabling customers, and continuously improving processes to enhance customer satisfaction and operational efficiency.

We're hiring a Technical CSM (with an AI focus) to join our Technical Adoption Success team, reporting to a regional leader. This is not a managerial role. Atlassian Technical CSMs are technical experts with Atlassian solutions, delivering guidance to drive value realization and adoption. Technical CSMs are accomplished at delivering performant technical guidance at scale, aligning product capabilities with business needs and desired outcomes. They partner with Pre-Sales, Post-Sales, and Product teams to provide solutions and technical guidance to help customers achieve their desired outcomes and goals.

You will help our strongest promoters showcase their successes to their peers and serve as the tip of the spear in expanding the reach of AI and the Atlassian System of Work into new use cases and markets. Atlassian Technical CSMs aim to help customers get the most out of their Atlassian investment.

On your first day, we'll expect you to have:

• Discovery. Facilitate use case discovery workshops with customer teams to identify high-impact, high-value AI opportunities. Understand their workflows, pain points, and where Rovo agents and search can deliver measurable outcomes.

• Design. Co-build custom Rovo agents and configure third-party connectors alongside customer teams. Customers are hands-on keyboard. Design solutions tailored to their workflows using the Atlassian platform (Jira, Confluence, Rovo Studio).

• Deploy. Guide customers from sandbox to production. Validate that agents are performing, connectors are flowing data, and teams are enabled to iterate and scale independently post-engagement.

• Collaborate. Work with Account Teams and Customer Success Managers (CSMs) to plan customer-specific activation journeys and hand off for sustained growth.

• Advocate. Meet with Rovo Product, Engineering, and AI teams to surface product friction, share field patterns, and improve the adoption motion.

• Travel up to 15% domestically and internationally for events and customer meetings.

Your background

• Customer Success & Experience: 3-5 years in Customer Success or account management, managing Enterprise customers with complex SaaS portfolios.

• Technical Aptitude: Experience with AI platforms, the Atlassian ecosystem (Jira, Confluence, Rovo), and technical product demos. Familiarity with building AI agents, prompt engineering, and configuring integrations between enterprise knowledge sources and AI systems. Hands-on experience helping organizations adopt and operationalize AI tools in production environments.

• Solution Area Expertise: Specialized knowledge in enterprise workflows across product development, IT service management, or business operations. Understanding how AI agents and automation can improve processes such as incident response, backlog management, knowledge discovery, and cross-team collaboration. Familiarity with third-party connector ecosystems (Google Drive, SharePoint, Slack, GitHub, etc.).

• Product Mindset & Communication: Strong product mindset, able to shape technical solutions for business impact, and comfortable owning problems end-to-end from discovery to deployment. Effective communicator who can influence stakeholders and explain AI concepts to varied audiences. Delivers durable solutions but can quickly prototype when needed. Ability to translate AI capabilities into tangible outcomes for non-technical stakeholders.