# Senior, Internal Audit AI Enablement & Automation

**Company:** [Okta](https://hotfix.jobs/companies/okta)
**Location:** San Francisco, CA
**Role:** Other
**Salary:** $104k – $161k/yr
**Experience:** 3+ years
**Skills:** internal audit, AI Automation, sox testing, cisa, auditboard, workiva, Claude, gemini, ChatGPT, Scripting, api, no-code tools, cloud auditing, ai governance
**Posted:** 2026-07-22

> Own the build, adoption, and measurement of Okta Internal Audit's AI automation program. Build AI tools from auditor problem statements, maintain impact dashboards, coordinate working groups, drive team participation, and represent IA in company-wide AI initiatives. Requires 3-6 years audit experience, hands-on AI tool experience, and relevant certifications.

## Job Description

## What You Will Own

### Automation Delivery
- Build and maintain AI automations across all Internal Audit functions using the department's existing AI Hub and SOX testing engine.
- Manage the problem statement intake pipeline, providing clear disposition (built, deferred, or declined with rationale) for every submission.
- Prioritize the backlog using impact, frequency, and build complexity.
- Maintain visibility into open problem statements.

### Measurement & Reporting
- 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.

### Working Group Coordination
- Maintain regular check-ins with each Working Group.
- Coordinate the Bi-Weekly Showcase cadence.
- Track each group against its phased plan.
- Flag delivery risk early and assist Working Group leads in sequencing deliverables.

### Individual Contributor Activation
- Track individual participation against department expectations.
- Reach out directly one-on-one to any team member with no recorded participation.
- Lead every team communication with benefits of participating.

### Culture, Knowledge Management & External Collaboration
- Maintain the AI Hub knowledge repository and AI Learning Catalog, keeping resources current 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 learnings and returning external intelligence back into the IA tool-building program.

## What You Bring
- CPA, CIA, CISA, or other relevant certification (active or in progress); CISA preferred.
- 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.
- Demonstrated ability to build or operate AI tools, automations, or structured prompt workflows applied to real audit work.
- Demonstrated ability to represent a team or function in cross-functional settings and present to audiences outside Internal Audit.
- Comfortable managing multiple concurrent workstreams with defined deliverables and deadlines.
- Strong written communication skills to translate technical output into plain-language narratives.
- Hands-on experience with AI productivity tools (Claude, Gemini, ChatGPT, or equivalent).

## What Sets You Apart
- 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.
- 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).

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