AI Journey Operations Manager

Secure Every Identity, from AI to Human

Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

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