Associate Director - Cyber Security (AI & Data Science)

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
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.
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
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
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
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.
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.
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.
Understanding of AI risks, model security and AI governance.
Technical Leadership
Ability to translate emerging AI technologies into production-grade cybersecurity capabilities.
Experience with cloud platforms and modern security architectures.
Understanding of APIs, microservices, containers and DevSecOps.
Experience integrating AI with enterprise security platforms.
Governance & Risk
Knowledge Of Relevant Frameworks Such As:
NIST Cybersecurity Framework
NIST AI RMF
Zero Trust Architecture
ISO 27001
SOC 2
GDPR / CCPA
PCI DSS
SOX / ITGC
Industry-specific cybersecurity regulations
Preferred Qualifications
Master’s degree in Cybersecurity, Computer Science, AI, Technology or related discipline.
CISSP / CISM / CCSP or equivalent certification.
Experience building cybersecurity AI capabilities from the ground up.
Experience with AI agents / autonomous security operations.
Experience in financial services, technology, fintech or other highly regulated industries.
Published research, patents, conference presentations or thought leadership in Cybersecurity/AI is a plus.
Experience working with cybersecurity startups and emerging technologies is desirable.
Related Skills
Collaboration, Continuous Improvement Mindset, Data-Driven Business Intelligence, Data Engineering/Analytics, Data Visualization, Predictive Mo

Work arrangement
No