What you'll do
In this role, you’ll join the Customer Success Architect team within Sales and Success as a CSA (AI-Service Management). This is an individual contributor role reporting to a regional leader. You'll help enterprise customers adopt Atlassian's AI-powered Service Collection: Jira Service Management (JSM), Customer Service Management, Assets, and Rovo Service Agents.
You'll lead time-boxed technical engagements and build solutions alongside customers, helping them turn traditional service desks into modern, AI-first service operations. Working with enterprise IT and business service leaders, you'll assess how they work today and co-design workflows across request, incident, problem, change, and asset management. You'll also help customers put autonomous and assisted AI experiences into production.
As a technical expert in Atlassian solutions, you'll deliver effective guidance at scale to help customers increase adoption and get more from their investment. The work involves connecting product capabilities with customers' business needs and desired outcomes. You'll partner with Pre-Sales, Post-Sales, and Product teams to provide solutions and technical guidance that help customers reach their goals.
You'll also help our strongest customer promoters share their successes with peers. As part of that work, you'll lead efforts to expand the Atlassian System of Work into IT, enterprise functions including HR, Facilities, Legal, and Finance, and customer service use cases.
On your first day, we'll expect you to have:
Discovery: Assess customers' service maturity and AI readiness across IT Service Management (ITSM), Enterprise Service Management (ESM), and Customer Service Management (CSM). Review ticket volume data, recurring requests, and knowledge health to find high-impact opportunities for deflection and automation.
Design: Work with customers to design AI-first service workflows, including conversational request channels in Slack and Teams, multi-tier queues, change risk models, and Assets/CMDB schemas. Configure and fine-tune Rovo Service Agents for automated triage, deflection, smart routing, and context generation.
Deploy: Help customers move from pilot to production. Validate deflection rates, agent accuracy, SLAs, alerting and on-call processes, and automated change policies. Establish continuous learning loops so service teams can monitor, refine, and scale AI agents independently.
Collaborate: Work with Account Teams, Customer Success Managers, and Service Collection specialists on technical activation plans. Help customers modernize from legacy tools such as ServiceNow, Zendesk, and BMC, or from standalone Opsgenie.
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 with the JSM, Assets, and Rovo engineering and product teams.
Travel up to 15% domestically and internationally for events and customer meetings.
Your background
Customer Success & Experience: 3-5 years in Customer Success, technical consulting, or solutions architecture, managing Enterprise customers with complex SaaS portfolios in IT or service operations.
Technical Aptitude: Hands-on experience implementing Jira Service Management. Familiarity with other Service Management products, such as ServiceNow, Zendesk, and BMC. Practical experience configuring conversational AI, virtual service agents, automated triage, and workflow automation. Experience with Assets/CMDB modeling, API integrations (monitoring, chat, CRM), and optimizing knowledge sources (Confluence) for AI retrieval.
Solution Area Expertise: Deep knowledge of IT service management, service management across business functions, and ITIL 4 practices (incident, problem, change, request, knowledge, and asset/configuration management). Understanding of Knowledge-Centered Service (KCS) principles. ITIL 4 Foundation certification or higher required.
Product Mindset & Communication: Strong product mindset with the ability to translate technical AI capabilities into clear business outcomes (deflection, MTTR reduction, CSAT) for IT leaders and executive stakeholders. Comfortable balancing rapid agent prototyping with enterprise-grade governance and reliability.