Senior Manager, Global AI Security

The Manager, Global AI Security is responsible for defining and driving the organization's AI security strategy, standards, and safeguards across the enterprise, while leveraging AI to strengthen cybersecurity capabilities and resilience.

As the organization's AI Security Subject Matter Expert (SME), the role ensures that artificial intelligence technologies are deployed securely, AI-related cyber risks are effectively identified and managed, and Information Security teams adopt and utilize AI capabilities to enhance threat detection, security operations, risk management, and defensive controls.

Reporting to the Global Information Security Director and working closely with Enterprise Architecture, Data & AI teams, Legal, Compliance, and business stakeholders at global and regional levels, the Manager, Global AI Security provides technical leadership and governance oversight for AI-related security risks while enabling secure innovation and business value creation.

The role combines strategic leadership with hands-on technical expertise in AI security architecture, AI threat modeling, AI red teaming, and emerging AI-enabled cyber threats.

Key Responsibilities

AI Security Strategy and Architecture

• Develop and maintain the enterprise AI Security Strategy.

• Define security requirements and architectural principles for AI systems, applications, agents, and machine learning platforms.
• Establish minimum security standards for internally developed and third-party AI solutions.
• Review and approve AI solution architectures from a security perspective.
• Provide security guidance throughout the AI development lifecycle.
• Collaborate with Enterprise Architecture teams to ensure secure adoption of AI technologies.

AI Risk Management

• Maintain and evolve the AI Cybersecurity Risk Taxonomy and associated control library together with the Information Security GRC team.
• Identify, assess and prioritize AI-specific cyber risks.
• Develop risk assessment methodologies for AI use cases and AI-enabled business processes.
• Monitor the evolving AI threat landscape and translate emerging threats into actionable security controls.
• Support enterprise risk management processes related to AI technologies.

AI Security Standards and Controls

• Develop and maintain AI Security Standards, Guidelines and Procedures.
• Align security requirements with recognized industry frameworks and best practices.
• Define security requirements covering:

- Generative AI and Large Language Models (LLMs)
- AI agents
- Retrieval-Augmented Generation (RAG)
- Model hosting environments
- AI supply chain security
- Sensitive data handling
- Third-party AI services

AI Red Teaming and Security Assurance

• Establish and manage the enterprise AI Red Teaming Program.
• Coordinate technical assessments of AI solutions prior to production deployment.
• Track remediation and improvement activities resulting from AI security assessments.
• Collaborate with external partners to define and adopt testing methodologies for:

- Prompt injection
- Jailbreak attacks
- Data poisoning
- Model manipulation
- Model extraction
- Agent abuse
- Unauthorized data disclosure

AI in Cyber Defense

• Identify opportunities to leverage AI capabilities within cybersecurity operations.
• Partner with Cyber Defense and SecOps teams to evaluate and deploy AI-driven security capabilities.
• Assess risks and benefits of AI-assisted security tools.
• Develop governance and measurement approaches for defensive AI use cases.
• Promote effective and responsible use of AI within security operations.

Awareness and Capability Building

• Develop and maintain enterprise AI security awareness and training programs.
• Educate technical teams regarding AI threats, attack techniques and defensive practices.
• Provide subject matter expertise to security teams, architects, developers and business stakeholders.
• Support development of AI security knowledge and capabilities across regional security organizations.

Governance and Stakeholder Engagement

• Act as the primary Information Security subject matter expert for AI-related security matters.
• Partner with Data & AI teams, Legal, Compliance, Procurement and Enterprise Architecture functions.
• Support AI governance forums, steering committees and security review boards.
• Provide regular status updates and risk reporting to senior leadership.
• Represent Information Security in strategic AI initiatives and enterprise programs.

Required Qualifications

Experience

• Minimum 10 years of experience in Information Security, Cybersecurity or Security Architecture.
• Minimum 3 years of experience in AI, machine learning, emerging technologies or cloud-based AI platforms.
• Experience with developing enterprise security standards and controls.
• Experience with conducting security architecture reviews and threat modeling activities.
• Experience with influencing senior stakeholders and driving cross-functional initiatives in global organizations.

Technical Knowledge

• Strong understanding of:

- LLMs and generative AI technologies
- AI agents and agentic architectures
- Retrieval-Augmented Generation (RAG)
- Machine Learning and model lifecycle concepts
- AI security threats and attack techniques
- Secure software development practices
- Cloud security architecture
- Identity and Access Management
- Data protection and privacy controls
- Security architecture principles

• Knowledge of:

- Prompt injection attacks
- Model poisoning
- Model theft and extraction
- Adversarial machine learning
- AI red teaming
- AI supply-chain security
- Autonomous agent security
- AI-enabled cyber threats

Preferred Qualifications

• ISSP
• CAISP
• AAISM
• AAIR
• SANS AI Security-related certifications
• Microsoft AI or Azure AI certifications
• Relevant AI security or machine learning security coursework

Critical Competencies

• Leadership

- Strategic thinking
- Influencing without authority
- Stakeholder management
- Global collaboration
- Program leadership

• Technical
  
  - Security architecture
  - Threat modeling
  - Risk assessment
  - Security control design
  - AI security testing

• Business

- Risk-based decision making
- Executive communication
- Policy development
- Technology governance
- Change management