Senior, Internal Audit AI Enablement & Automation

1. → Automation Delivery - This is the core of the role. Everything else supports it.

Build and maintain AI automations across all Internal Audit functions using the department's existing AI Hub and SOX testing engine as the foundation. Manage the problem statement intake pipeline, acknowledging every submission with a clear disposition (built, deferred, or declined with rationale) and prioritizing the backlog using impact, frequency, and build complexity. Keep the intake process simple, and maintain visibility into open problem statements so the team knows submissions go somewhere.

1. → Measurement & Reporting - This role owns the data that makes recovered hours real and attributable.

Maintain the AI Impact Dashboard with accurate, function-level attribution. Protect the integrity of the measurement methodology, tracking protocols, time categories, and verification standards. Surface delivery risk early, contribute to periodic AI Value Reports, and support executive and Audit Committee-ready materials that translate hours saved into dollar value and strategic audit impact.

1. → Working Group Coordination - The Working Groups are the primary vehicle for team-wide adoption. This role keeps them moving.

Maintain regular check-ins with each Working Group, coordinate the Bi-Weekly Showcase cadence, and track each group against its phased plan. Flag delivery risk early and assist Working Group leads in sequencing deliverables against the overall automation backlog.

1. → Individual Contributor Activation - Broad participation is essential. This role removes the friction that prevents it.

Track individual participation against department expectations. Reach out directly one-on-one, not via group reminder, to any team member with no recorded participation. Lead every team communication with what auditors gain from participating, not what is required of them.

1. → Culture, Knowledge Management & External Collaboration - This role sustains momentum through recognition, a maintained knowledge base, and active participation in company-wide AI initiatives.

Maintain the AI Hub knowledge repository and AI Learning Catalog, keeping resources current, connected to real audit tasks, and tracked at the individual level. Follow up individually with anyone below learning pace.

Represent Internal Audit in cross-functional and company-wide AI initiatives — contributing IA's automation learnings to broader enterprise conversations and returning external intelligence back into the IA tool-building program. Success is measured by bidirectional value: what IA contributes to the enterprise, and what the enterprise contributes back.

• CPA, CIA, CISA, or other relevant certification (active or in progress); CISA preferred given the IT audit and automation crossover this role demands
• 3–6 years of internal audit experience across at least two disciplines (internal audit, IT audit, SOX business process, SOX ITAC/ITGC, or data analytics)
• Sufficient audit technical depth to build automations that meet Internal Audit quality standards — including evidence documentation, workpaper integrity, and SOX testing requirements across financial and IT controls
• Demonstrated ability to build or operate AI tools, automations, or structured prompt workflows applied to real audit work — not just coursework or certifications
• Demonstrated ability to represent a team or function in cross-functional settings — can prepare, present, and defend a point of view to audiences outside Internal Audit, including Finance leadership and enterprise program stakeholders
• Comfortable managing multiple concurrent workstreams with defined deliverables and deadlines
• Strong written communication skills — able to translate technical output into plain-language narratives for non-technical audiences
• Hands-on experience with AI productivity tools (Claude, Gemini, ChatGPT, or equivalent)

• Big 4 public accounting or IT audit advisory experience
• Experience with audit management platforms (AuditBoard, Workiva, or equivalent)
• Experience coordinating working groups, project timelines, or cross-functional initiatives
• Experience representing a function or team in cross-functional working groups, communities of practice, or enterprise-level program networks
• Background in learning content curation or enablement program support
• Familiarity with basic scripting, API concepts, or no-code/low-code workflow tools
• Experience auditing within cloud-based or SaaS environments
• Awareness of AI governance, ethics, and emerging risks (model bias, data privacy, hallucination risks)

• Builder Mentality: Ships working tools on a predictable cadence — does not wait for perfect requirements, engineering support, or top-down direction. Closes problem statements with a disposition, not a placeholder
• Precision Over Volume: Tracks what matters and defends the measurement methodology when pressured to inflate numbers. Knows the difference between hours recovered and hours verified — and never conflates them
• Say/Do Ratio: Intake SLAs are met. Working Group milestones are hit. What is committed to leadership is what is delivered — on time, at the quality level stated. Escalates delivery risk early with data, not after the deadline passes
• Offer-First Communication: Leads every team message with what auditors gain from participating, not what is required of them. Understands that adoption is earned, not mandated
• Intellectual Curiosity: Proactively tracks the AI tool landscape — brings new capabilities, prompt patterns, and automation approaches to the team before they are asked for. Curiosity is directed, not scattered: every new tool evaluated connects to a specific audit task
• Problem-Solving Transparency: Can walk any team member through how a tool was built or a prioritization decision was made — not just what the output is. Teaches the method, not just the result
• Intellectual Honesty: Comfortable saying "this automation didn't work" or "I don't know how to build that yet" — and documents both outcomes with the same rigor as successes. Failure data improves the backlog
• Stakeholder Navigation: Maintains credibility with Working Group leads, IA leadership, and cross-functional partners when timelines shift or tools underdeliver. Resolves friction without escalating unnecessarily
• Ownership: Takes end-to-end accountability for the automation program — from intake through impact reporting — without requiring follow-up from the supervising manager to close open items
• Adaptability: Adjusts build priorities as audit cycle demands shift without losing sight of annual targets. Comfortable with ambiguity in a program that is still being built while it runs
• Deadline Accountability: Treats intake SLAs and Working Group milestone commitments as non-negotiable floors, not targets. Surfaces risk to the supervising manager with supporting data — before the deadline, not after
• Calm Under Pressure: Maintains even temperament when adoption is slow, tools break, or leadership asks hard questions about impact. The team wants to bring problems to this person, not hide them
• Enterprise AI Representation: Shows up to Finance and Company AI Champions programs as a prepared, credible voice for Internal Audit — not just an attendee. Returns external intelligence (new tools, peer use cases, company AI direction) into the IA program within the same quarter it is learned

This role operates in Okta's hybrid work environment. You are expected to go to the San Francisco office two days per week.

#LI-hybrid 

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