Associate Director - Cyber Security (AI & Data Science)

About the job

Associate Director - Data Analytics Associate Director – Data Analytics will lead the implementation of enterprise analytics development work for both business intelligence and data engineering needs. The Data Analytics job manages multiple teams led by managers or team leaders that gather, analyze, interpret and visualize enterprise wide analytics data, identifying insights that ultimately inform business, customer experience, product development and marketing decisions. This job oversees the development of analysts in both Data Engineering and Business intelligence. This job owns adherence to the development of standards and controls, data quality and assurance, and implementing those standards across the entire team, and in conjunction with business partners in the US.

Key Responsibilities and Duties - Enforces policies and procedure in partnership with onshore analytics leaders to ensure consistent, reliable data output - educating and enforcing adherence of standards across the team

- Consults on the development of new standard operating procedures based on knowledge of existing and emerging analytics principles, theories and techniques to inform business decisions and the operating model

- Establish systems of controls and Quality Assurance to ensure adherence to data quality and automation in alignment with IT standards.

- Communicates with leadership on analytics matters to ensure enterprise-wide understanding of their contribution to a mature analytics organization’s success.

- Perform administrative and support activities including security administration, release management and troubleshooting

- Perform development activities from gathering requirements and designing solutions, through developing code / reports, to testing and release / deployment Educational Requirements - University (Degree) Preferred Work Experience - 5+ Years Required; 7+ Years Preferred Physical Requirements - Physical Requirements: Sedentary Work

Career Level 9PL

Job Description — Associate Director / Head of Cybersecurity AI Position Associate Director – Cybersecurity AI / Head of Cybersecurity AI Experience 12–15+ years in Cybersecurity, Information Security, AI Security, Security Engineering, or related technology leadership roles. Role Overview We are looking for a strategic and hands-on Cybersecurity AI leader to define and drive the organization’s strategy for applying Artificial Intelligence and Agentic AI to cybersecurity , while establishing security, governance, and risk controls for AI adoption across the enterprise. The role will lead the development of AI-enabled cybersecurity capabilities , including AI-driven SOC, security automation, threat detection, identity and access intelligence, data security, insider-threat detection, third-party risk, vulnerability management, security engineering, and cyber risk analytics. The leader will also establish a Zero Trust–aligned security framework for AI and autonomous agents , covering non-human identities, intent, access, data usage, model interactions, tool invocation, and autonomous actions.

Key Responsibilities 1. Cybersecurity AI Strategy

- Define and execute the enterprise Cybersecurity AI strategy and roadmap .

- Identify high-value cybersecurity use cases for GenAI, ML and Agentic AI.

- Build business cases, investment roadmaps and measurable ROI for AI-driven security transformation.

- Establish responsible and secure adoption of AI across Cybersecurity. 2. AI for Cybersecurity Lead AI transformation across:

- AI-enabled SOC and Security Operations

- Threat detection and investigation

- Incident response automation

- Security orchestration and autonomous response

- Vulnerability and exposure management

- Identity and access intelligence

- Insider-threat detection

- Data Loss Prevention and data classification

- Third-party / supply-chain cyber risk

- Threat intelligence

- Security analytics and cyber-risk dashboards

- Application and cloud security

- Security engineering automation 3. Security of AI / AI Security Define controls and architecture for securing enterprise AI environments, including:

- GenAI and LLM security

- AI applications and copilots

- Agentic AI

- AI agents and non-human identities

- Model and API security

- Prompt injection and data leakage

- AI supply-chain/model risks

- RAG and vector database security

- AI data governance and lineage

- Model access and authorization

- AI red teaming and adversarial testing

- AI runtime monitoring 4. Agentic AI & Zero Trust Establish a Zero Trust security model for autonomous AI agents , covering: Identity → Intent → Access → Data → Action → Continuous Validation Key areas include:

- Non-human identity management

- Agent authentication and authorization

- Role/attribute-based access control

- Just-in-time and least-privilege access

- Agent-to-agent communication

- Tool/API access governance

- Data access and classification

- Autonomous action controls

- Human-in-the-loop controls

- Agent activity monitoring and auditability

- Dynamic risk-based policy enforcement

- Blast-radius containment 5. AI Governance & Risk

- Establish AI security standards, policies and control frameworks.

- Partner with Legal, Privacy, Risk, Compliance, Data and Enterprise Architecture teams.

- Develop AI risk assessment and security review processes.

- Map controls to relevant regulatory and industry frameworks.

- Define AI security metrics, KRIs and executive dashboards. 6. Cybersecurity Engineering & Transformation

- Lead architecture and implementation of AI-enabled security platforms.

- Integrate AI capabilities across existing SOC, SIEM, SOAR, IAM, DLP, EDR, CSPM and GRC ecosystems.

- Drive automation and reduction of manual security operations.

- Evaluate emerging cybersecurity AI technologies, startups and platforms.

- Build internal AI security capabilities where commercial solutions are insufficient. 7. Leadership & Stakeholder Management

- Lead a team of cybersecurity, AI security, security engineering and data/AI specialists.

- Partner with CISO, CIO, CTO, Chief Data Officer, Chief AI Officer and business leadership .

- Present AI security strategy, risk and investment requirements to senior leadership.

- Develop strategic partnerships with technology vendors, startups and research organizations.

- Mentor and develop senior cybersecurity and AI talent.

Required Experience & Skills Core Cybersecurity

- 12–15+ years of cybersecurity / information security experience.

- Strong understanding of security architecture, SOC, IAM, AppSec, Cloud Security, GRC and security engineering.

- Experience leading enterprise-scale cybersecurity transformation.

- Strong understanding of Zero Trust principles. AI / ML

- Strong understanding of: - Generative AI

- LLMs

- Machine Learning

- RAG

- AI agents

- Agentic workflows

- AI APIs and orchestration

- AI security architecture

- Experience implementing AI/ML solutions in cybersecurity .