AI Journey Operations Manager, Okta

• 7+ years of experience in B2B demand generation, revenue operations, Sales operations, xDR operations, marketing operations, growth operations, or a related GTM operations discipline
• Experience with AI SDR or AI xDR platforms, conversational marketing, automated qualification, or agent-assisted engagement
• Demonstrated experience designing or operationalizing AI-assisted, automated, or rules-based qualification and engagement workflows in a B2B GTM environment. This may include AI SDR/xDR, conversational marketing, automated lead qualification, intelligent routing, next-best-action workflows, or comparable AI-enabled buyer engagement models
• Strong understanding of how Marketing, xDR, and Sales processes connect to opportunity creation and pipeline progression
• Experience defining business rules and translating them into technical workflow requirements
• Experience partnering directly with xDR leadership, Sales Operations, Revenue Operations, and Sales stakeholders
• Strong analytical ability, including experience evaluating conversion, acceptance, progression, and pipeline performance
• Ability to lead a complex cross-functional capability without direct authority
• Strong documentation, governance, and operating-process design skills
• Familiarity with Qualified, Outreach, Salesforce, Marketo, Common Room, Clay, or comparable GTM platforms

Desirable

• Okta is building an AI-enabled demand engine that uses signals, automation, and intelligent engagement to identify, qualify, route, and progress the right buyers more effectively
• The AI Journey Operations Manager will own the business strategy, qualification framework, routing logic, operating model, and performance optimization for AI-assisted xDR capabilities across the Global Demand Center
• This role is not primarily a platform administration or workflow-build role
• It is a senior, cross-functional capability-owner role responsible for determining how AI-assisted qualification and engagement should operate, how it connects to human xDR and Sales follow-up, and how it contributes to measurable funnel and pipeline outcomes
• The ideal candidate combines AI-enabled GTM experience, xDR/Sales process knowledge, demand generation, revenue operations, and journey strategy
• They can translate business priorities into qualification logic, routing rules, AI engagement workflows, handoff requirements, measurement frameworks, and ongoing optimization plans
• Own AI xDR qualification strategy
• Define qualification frameworks for AI-assisted engagement across priority inbound, account-based, product-led, customer, and signal-triggered motions
• Establish the fit, behavior, intent, engagement, and business-context criteria used to determine whether a lead or account should be engaged, progressed, routed, recycled, or suppressed
• Partner with Revenue Operations, xDR leadership, Sales Operations, and Marketing to align AI qualification logic with lifecycle definitions and Sales acceptance requirements
• Establish governance for qualification-model changes, exceptions, and regional or segment-specific variations
• Design routing, handoff, and disposition models
• Define AI qualification criteria based on fit, intent, behavior, engagement, account context, and business priority. Partner with Sales, xDR, Revenue Operations, Marketing Operations, Growth, and Journey teams to determine when AI should engage, when a human xDR or seller should take over, and when an account should move into nurture, suppression, or another follow-up path
• Design next-best-action rules, handoff thresholds, escalation paths, service-level expectations, and exception handling
• Establish consistent acceptance, rejection, disposition, recycling, and re-entry processes across Marketing, AI xDR, and Sales teams
• Identify and resolve leakage, latency, and ownership gaps between AI engagement and human follow-up
• Connect AI xDR to revenue outcomes
• Define how AI xDR performance will be measured across qualified engagement, human acceptance, meetings, opportunity creation, pipeline progression, and other agreed funnel outcomes
• Partner with Revenue Operations and Analytics to establish reporting, attribution, and feedback loops
• Diagnose where AI-engaged leads and accounts stall or fail to progress and recommend changes to qualification, routing, handoff, or follow-up logic
• Use funnel data to prioritize use cases and determine where AI xDR should expand, change, or stop
• Lead the cross-functional operating model
• Serve as the primary business owner for AI xDR across Marketing, xDR, Sales, Revenue Operations, Sales Operations, and Journey Architecture
• Translate business policies and revenue-process requirements into specifications for technical builders and platform administrators
• Establish decision rights, governance, documentation, testing, launch readiness, and ongoing change-management processes
• Lead expansion planning across regions, segments, platforms, and use cases
• Guide workflow implementation
• Partner with Qualified, Outreach, CRM, marketing automation, and related platform owners to ensure workflows reflect approved qualification, routing, and handoff requirements
• Validate that implementation matches the intended business logic and revenue operating model
• Monitor workflow accuracy, operational compliance, and downstream outcomes
• Recommend technical or process changes based on funnel performance and stakeholder feedback
• How Success Will Be Measured:
• Accuracy and effectiveness of AI-assisted qualification
• Human xDR and Sales acceptance rates
• Speed and quality of AI-to-human handoffs
• Reduction in routing, ownership, and follow-up leakage
• Progression from AI engagement to meetings, opportunities, and pipeline
• Adoption and confidence among xDR, Sales, Marketing, and Revenue Operations stakeholders
• Scalability and governance of the AI xDR operating model