Lead AI & Technology Risk Auditor in United States at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead AI & Technology Risk Auditor based in United States.
This senior-level role sits at the intersection of internal audit, artificial intelligence, and emerging technology risk, with a strong focus on AI, generative AI, and advanced data-driven systems. The position is responsible for leading complex, high-impact audits across cloud, machine learning, and AI-enabled platforms, ensuring robust governance and control frameworks are in place. It offers the opportunity to shape audit methodologies for next-generation technologies while directly influencing enterprise risk strategy. The role works closely with senior stakeholders across technology and business functions to assess risk exposure and strengthen control environments. It also plays a key part in advancing audit transformation through automation, analytics, and AI-enabled tools. This is a highly visible leadership role that combines technical depth, strategic thinking, and mentorship within a rapidly evolving digital landscape.
- Lead complex technology and business audits with a focus on AI, generative AI, machine learning systems, and cloud-native environments, ensuring structured execution and timely delivery.
- Design and execute audit programs, including risk assessments, control identification, testing procedures, and documentation of findings across advanced technology ecosystems.
- Apply data analytics and AI-assisted audit techniques using tools such as Python, SQL, and visualization platforms to identify anomalies, trends, and root causes.
- Evaluate governance and controls for AI systems, including LLMs, agentic AI, prompt engineering safeguards, data privacy, and third-party AI providers.
- Drive agile audit execution by managing sprint cycles, resolving blockers, tracking progress, and ensuring alignment with audit objectives and timelines.
- Communicate audit insights clearly through sprint reviews and formal reporting, translating technical findings into actionable business recommendations.
- Collaborate with IT and business leadership to strengthen risk management practices and support enterprise-wide audit strategy and transformation initiatives.
- Mentor and coach audit team members, supporting capability development in AI literacy, analytics, and advanced audit methodologies.
Requirements:
- Bachelor’s, Master’s, or Doctorate degree in a relevant field with at least 5 years of professional experience in audit, risk, technology, or data-focused roles.
- Minimum 1 year of direct experience assessing, auditing, or working with AI/ML systems, data governance, or advanced analytics platforms.
- Professional certification such as CPA, CISA, CIA, CFE, or equivalent, or ability to obtain within 18 months.
- Strong understanding of AI/ML concepts including neural networks, NLP, generative AI, and modern AI architectures.
- Hands-on experience or familiarity with Python, SQL, or similar tools for data analysis and visualization.
- Knowledge of AI governance principles including fairness, transparency, accountability, explainability, and data privacy.
- Experience working in complex, matrixed environments with strong stakeholder management and communication skills.
- Ability to translate technical risk insights into clear audit findings and strategic recommendations.
Benefits:
- Competitive compensation package aligned with experience and qualifications.
- Comprehensive health, dental, and vision insurance coverage.
- Retirement savings plans and financial well-being programs.
- Flexible work arrangements with remote work support where applicable.
- Monthly connectivity reimbursement for eligible remote employees.
- Paid time off and well-being-focused leave policies.
- Professional development opportunities, including certifications and training in AI, data analytics, and audit innovation.
- Exposure to cutting-edge AI, cloud, and digital transformation initiatives within enterprise-scale environments.