Director of Data & AI Governance

Responsibilities

• Define and execute the enterprise Data & AI Governance, Risk, and Security strategy aligned with business and regulatory priorities
• Establish a governance operating model and stewardship integrating governance, risk, privacy, and access control disciplines
• Drive adoption of a “secure and compliant by design” framework across data platforms, AI models, and analytics solutions
• Lead enterprise data governance, including data ownership, stewardship, classification, and quality standards
• Establish governance frameworks for AI/ML models, including lifecycle management, explainability, and monitoring (bias, model & Agent drift)
• Define and enforce policies, standards, and controls for data and AI usage
• Develop and operationalize Data & AI risk management frameworks, including Data classification and handling, model risk, data risk, and third-party risk
• Ensure compliance with global regulations (e.g., GDPR, ITAR, EAR, export controls, emerging AI regulations)
• Lead risk assessments, audits, and regulatory engagements related to data and AI
• Embed governance controls into enterprise data platforms (e.g., EDW, data lakes, AI platforms)
• Own and drive Data & AI Audit readiness, compliance reporting, and regulatory response
• Define and implement data security and privacy architecture, including encryption, masking, tokenization, and anonymization
• Partner with Cybersecurity to ensure alignment with broader enterprise security strategy
• Oversee data privacy programs, including consent management, data minimization, and data subject rights
• Lead Responsible AI practices, including bias detection, fairness, transparency, and ethical use standards
• Establish approval, validation, and monitoring processes for AI models and GenAI solutions
• Mitigate risks such as AI model drift, hallucination, misuse, and AI whitewashing
• Enable self-service analytics and citizen development with appropriate guardrails and controls
• Drive enterprise-wide data literacy and governance adoption
• Build strong partnerships with business and technology leaders to embed governance into daily operations
• Lead and scale a high-performing organization across: Data & AI Governance, Risk and Compliance, Security, Privacy and Access Controls
• Define clear roles, accountability models, and performance metrics

Qualifications

• Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status.
• 12+ years of experience in data governance, cybersecurity, risk, compliance, or AI governance
• Proven leadership experience in building and leading enterprise-scale governance or security organizations
• Strong knowledge of: Data governance frameworks (e.g., DAMA-DMBOK), AI/ML governance and risk management, Data security and access control management
• Experience with cloud data platforms (e.g., Snowflake, Databricks, AWS/Azure/GovCloud)
• Deep understanding of regulatory environments (ITAR, GDPR, CCPA, industry-specific regulations such as aerospace/defense if applicable)
• Strong executive communication and stakeholder management skills
• Experience in highly regulated industries (e.g., aerospace, defense, finance, healthcare)
• Bachelor's Degree in Information Technology and Cybersecurity
• Familiarity with NIST AI Risk Management Framework, ISO 27001, SOC2
• Experience enabling data democratization with governance guardrails
• Strong executive communication and stakeholder management skills