AI Governance & CoE Lead

Veritas Search Group; Tustin (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Veritas Search Group seeks an experienced AI Governance and Center of Excellence Lead to establish and mature an enterprise AI governance program near Tustin, CA. The role partners with security, risk, compliance, legal, data, and business teams to implement policies, processes, and controls across the organization.

This hands-on leadership position focuses on building sustainable governance capabilities, coaching stakeholders, managing active AI use cases, and transitioning ownership to the

Qualifications

• Significant experience establishing and leading AI governance, cybersecurity governance, risk-management, compliance, or related enterprise programs.

Responsibilities

• Design and implement an enterprise AI governance operating model, including the program charter, roles and responsibilities, policies, standards, intake processes, prioritization criteria, and lifecycle-management procedures.
• Establish structured processes for identifying, evaluating, approving, deploying, monitoring, and retiring AI systems and use cases.
• Lead or co-lead recurring AI Center of Excellence meetings and coordinate activities across technical, security, compliance, risk, and business teams.
• Develop AI use-case intake and scoring methodologies based on business value, regulatory requirements, security exposure, data sensitivity, and operational risk.
• Conduct AI risk, security, privacy, and compliance reviews for vendor-provided AI capabilities, internally developed applications, and proposed business use cases.
• Partner with architecture and engineering teams to evaluate AI system design, data flows, human oversight, model security, and deployment controls.
• Develop and maintain AI policies, standards, playbooks, risk registers, model inventories, governance dashboards, and supporting documentation.
• Incorporate governance workflows into enterprise platforms such as ServiceNow, Jira, Confluence, or similar tools.
• Coach internal team members through structured meetings, working sessions, retrospectives, and capability assessments.
• Assign clear ownership for governance processes and jointly develop deliverables with the employees who will maintain them.
• Identify and address common program challenges, including disconnected tools, unclear accountability, excessive reliance on individual contributors, intake backlogs, and limited stakeholder participation.
• Create a structured transition plan that enables internal teams to independently manage the governance program.
• Track program performance, document decisions, maintain audit evidence, and report governance activities to executive stakeholders.
• Stay current on emerging AI regulations, governance standards, security risks, and responsible AI practices.

Skills

AI governance

Enterprise program leadership

Risk management

Compliance frameworks

Policy development

Stakeholder management

Cross-functional collaboration

Job description

This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted. This role is on-site near Tustin, CA.

Position Overview

We are seeking an experienced AI Governance and Center of Excellence Lead to establish, operationalize, and mature an enterprise artificial intelligence governance program.

This role will partner with technology, security, risk, compliance, legal, data, and business teams to create a structured approach for evaluating, approving, implementing, and monitoring AI solutions. The successful candidate will develop the governance framework while working directly with internal teams to ensure policies, processes, and controls are incorporated into day-to-day operations.

This is a hands-on program leadership position focused on building sustainable governance capabilities rather than producing point-in-time recommendations or documentation. The individual will help establish the program, coach internal stakeholders, manage active AI use cases, and transition long-term ownership to the organization.

Key Responsibilities

• Design and implement an enterprise AI governance operating model, including the program charter, roles and responsibilities, policies, standards, intake processes, prioritization criteria, and lifecycle-management procedures.
• Establish structured processes for identifying, evaluating, approving, deploying, monitoring, and retiring AI systems and use cases.
• Lead or co-lead recurring AI Center of Excellence meetings and coordinate activities across technical, security, compliance, risk, and business teams.
• Develop AI use-case intake and scoring methodologies based on business value, regulatory requirements, security exposure, data sensitivity, and operational risk.
• Conduct AI risk, security, privacy, and compliance reviews for vendor-provided AI capabilities, internally developed applications, and proposed business use cases.
• Partner with architecture and engineering teams to evaluate AI system design, data flows, human oversight, model security, and deployment controls.
• Develop and maintain AI policies, standards, playbooks, risk registers, model inventories, governance dashboards, and supporting documentation.
• Incorporate governance workflows into enterprise platforms such as ServiceNow, Jira, Confluence, or similar tools.
• Coach internal team members through structured meetings, working sessions, retrospectives, and capability assessments.
• Assign clear ownership for governance processes and jointly develop deliverables with the employees who will maintain them.
• Identify and address common program challenges, including disconnected tools, unclear accountability, excessive reliance on individual contributors, intake backlogs, and limited stakeholder participation.
• Create a structured transition plan that enables internal teams to independently manage the governance program.
• Track program performance, document decisions, maintain audit evidence, and report governance activities to executive stakeholders.
• Stay current on emerging AI regulations, governance standards, security risks, and responsible AI practices.

Required Qualifications

• Significant experience establishing and leading AI governance, cybersecurity governance, risk-management, compliance, or related enterprise programs.
• Demonstrated experience building governance programs from the ground up and transitioning ownership to internal teams.
• Strong working knowledge of AI governance and risk-management frameworks, including ISO/IEC 42001, ISO/IEC 23894, or the NIST AI Risk Management Framework.
• Experience working in a regulated industry such as healthcare, financial services, insurance, government, or another highly controlled environment.
• Strong understanding of AI security, privacy, risk, compliance, data governance, and responsible AI principles.
• Ability to evaluate technical topics such as human-in-the-loop controls, model manipulation, model poisoning, data exfiltration, third-party AI risk, and sensitive-data exposure.
• Experience assessing both internally developed AI systems and AI functionality provided through third-party vendors.
• Ability to communicate effectively with executive leaders, architects, engineers, security professionals, compliance teams, legal teams, and business stakeholders.
• Strong facilitation, program-management, documentation, coaching, and stakeholder-management skills.
• Ability to convert policies and governance requirements into repeatable operational workflows and measurable controls.

Preferred Qualifications

• Experience implementing governance workflows within ServiceNow, Jira, Confluence, governance-risk-and-compliance platforms, or similar enterprise systems.
• Previous experience in a player-coach, consulting, fractional leadership, transformation, or capability-transfer role.
• Experience developing AI inventories, risk-classification models, governance dashboards, control libraries, and approval workflows.
• Knowledge of applicable privacy, cybersecurity, and industry-specific regulatory requirements.
• Relevant certifications such as CISSP, CISM, CRISC, AIGP, or comparable credentials.