Job Description of Chief AI Officer

1. Position Summary

The CAISO is the senior executive responsible for securing the organization’s AI lifecycle. This role bridges the gap between data science, cybersecurity, and regulatory compliance. The CAISO will define the “Guardrails” that allow us to innovate with Generative AI and ML while minimizing risks related to adversarial attacks, model bias, hallucinations, and regulatory non-compliance (EU AI Act, ISO 42001, NIST AI RMF).

2. Key Responsibilities

A. Strategy & Governance

• Framework Implementation: Architect and own the AI Management System (AIMS) in alignment with ISO 42001.
• Policy Development: Author and enforce policies on Acceptable Use of AI, prohibiting “Shadow AI” and defining data privacy standards for LLM interactions.
• Risk Tolerance: Define the organization’s risk appetite for AI adoption (e.g., approval thresholds for probabilistic vs. deterministic systems).

B. AI Security Operations (Securing the Model)

• Adversarial Defense: Implement defenses against prompt injection, model inversion, data poisoning, and membership inference attacks.
• Red Teaming: Lead internal or third-party “Red Team” exercises to jailbreak company models and identify safety failures before deployment.
• Supply Chain Security: Vet third-party models (e.g., OpenAI, Anthropic, HuggingFace) and datasets for vulnerabilities and licensing risks.

C. Compliance & Ethics (Trustworthy AI)

• Regulatory Compliance: Ensure all AI systems meet the requirements of the EU AI Act (specifically for High-Risk systems) and local regulations in [Region/Country].
• Bias & Fairness: Oversee the technical evaluation of models for demographic bias and disparate impact prior to release.
• Transparency: Maintain a “Model Registry” and algorithmic transparency logs to ensure explainability of automated decisions.

D. Collaboration & Training

• Data Science Liaison: Embed security champions within data science teams to ensure “Security by Design” in MLOps pipelines.
• Workforce Training: Develop training modules on AI security risks (e.g., “Why you shouldn’t paste proprietary code into public chatbots”) for the general workforce.

3. Qualifications

Education:

• Master’s degree in Computer Science, Cybersecurity, Data Science, or Law.
• PhD in Machine Learning or related field is a plus.

Experience:

• 10+ years in Cybersecurity, Risk Management, or Data Privacy.
• 3+ years specifically focused on AI/ML technologies (e.g., experience with LLMs, MLOps, or algorithmic auditing).
• Proven experience implementing frameworks like NIST AI RMF, ISO 27001, or ISO 42001.

Technical Skills:

• Understanding of ML architectures (Transformers, Neural Networks) and the specific attack vectors against them.
• Familiarity with privacy-preserving technologies (Differential Privacy, Federated Learning).
• Knowledge of Python, TensorFlow, or PyTorch is highly desirable.

Certifications (Preferred):

• BCAA UK Certified AI Security Officer
• BCAA UK Certified AI Governance Officer

4. Key Performance Indicators (KPIs)

The success of the CAISO will be measured by:

1. Risk Reduction: Reduction in critical vulnerabilities found in AI models post-deployment.
2. Compliance Rate: 100% adherence to regulatory filings and ISO 42001 audit requirements.
3. Deployment Velocity: Time-to-approval for new AI projects (balancing speed with safety).
4. Incident Response: Mean Time to Detect (MTTD) adversarial attacks on AI interfaces.