Serve as the lead technical advisor for Internal Audit across cybersecurity, cloud, platform environments, and AI/ML systems, including Responsible AI governance
Partner with audit teams to scope, design, and execute complex technology audits
Provide credible challenge and guidance to engineering and security stakeholders
Translate technical risks into clear, actionable insights for executive leadership and the Audit Committee
Lead the modernization of Internal Audit through AI-enabled audit techniques, automation, and continuous auditing capabilities
Identify and deploy solutions that increase efficiency, expand coverage, and elevate insight
Help define the future-state audit model aligned to F5’s technology landscape
Enable data-driven auditing and control telemetry across the audit lifecycle
Develop tools and approaches that deliver real-time and predictive risk insights
Enhance executive and Audit Committee reporting to be forward-looking and decision-oriented
Build trusted relationships with Engineering, Product, Security, and Risk leadership
Act as a thought partner on emerging risks, including AI and platform resilience
Influence enterprise conversations on technology risk, governance, and innovation
Operate with independence and objectivity while enabling business velocity
Mentor and upskill audit team members on cyber, AI, and modern engineering practices
Requirements
15+ years of experience in technology-focused Internal Audit or in technical program management, engineering, or security roles with audit/advisory exposure
Deep expertise in cybersecurity and cloud environments
Experience with AI / Responsible AI risk management
Strong understanding of modern SDLC, DevSecOps, and platform architectures
Proven ability to translate complex technical risks into business insights
Experience advising engineering and security stakeholders in a technology company
Strong executive communication and influencing skills
Experience developing or deploying AI or automation solutions for audit or risk functions (preferred)
Experience with data analytics or visualization tools (e.g., Python, SQL, Tableau, Power BI) (preferred)
Familiarity with Kubernetes, containerized environments, and major cloud platforms (preferred)