Director, AI Governance Risk & Responsible AI

Acosta•Lewisville, TX

About The Position

The Director, AI Governance, Risk & Responsible AI will operationalize Acosta Group’s AI governance model by turning policy, risk expectations, and Responsible AI principles into practical controls embedded in the AI delivery lifecycle. This leader will establish governance processes for AI use cases, tools, vendors, models, agents, copilots, data usage, lifecycle monitoring, and production readiness. The role supports the AI CoE operating model of central guardrails, federated execution, and portfolio-driven scaling by enabling Acosta Group to innovate with speed while maintaining appropriate oversight, accountability, security coordination, and evidence of control compliance.

Requirements

Bachelor’s degree in information technology, Computer Science, Cybersecurity, Data Science, Risk Management, Law, Business Administration, or a related field; advanced degree preferred.
12 or more years of experience in governance, risk management, compliance, technology risk, cybersecurity governance, privacy, enterprise controls, data governance, or related disciplines.
5 or more years of leadership experience overseeing governance, risk, compliance, technology controls, model oversight, Responsible AI, data governance, or regulated technology programs within a large enterprise environment.
Strong understanding of Artificial Intelligence, Generative AI, machine learning, agentic AI systems, copilots, intelligent automation, foundation models, model lifecycle management, and associated enterprise risks.
Experience designing and implementing governance frameworks, control structures, risk assessment methodologies, approval workflows, policy enforcement mechanisms, and enterprise oversight processes.
Demonstrated experience establishing and operationalizing Responsible AI programs, including controls related to fairness, transparency, explainability, accountability, human oversight, privacy, and ethical AI use.
Experience evaluating and managing AI-related risks across security, privacy, legal, regulatory, operational, reputational, and model performance domains.
Knowledge of applicable regulatory, privacy, cybersecurity, risk, and governance frameworks, including emerging AI regulations and industry standards.
Experience reviewing and governing third-party AI vendors, foundation models, SaaS AI platforms, copilots, and AI-enabled technologies.
Ability to partner effectively with Legal, Compliance, Privacy, Cybersecurity, Enterprise Risk, Data, Technology, Procurement, Internal Audit, and business stakeholders.
Experience translating governance policies and standards into practical operating procedures, controls, templates, review processes, training materials, and implementation guidance.
Excellent written, verbal, and executive communication skills, including the ability to clearly explain AI risks, governance requirements, compliance obligations, and mitigation strategies to technical and non-technical audiences.

Nice To Haves

Preferred Certifications such as CRISC, CISM, CISSP, CIPP, CDPSE, CGEIT, AI Governance Professional, Responsible AI certifications.

Responsibilities

Operationalize Acosta Group’s AI policies, Responsible AI principles, governance standards, and lifecycle controls across AI initiatives.
Establish and maintain AI governance workflows for intake, risk classification, review, approval, monitoring, change management, and retirement.
Partner with Legal, Compliance, Cybersecurity, Privacy, Risk, Data Governance, Technology, and business leaders to embed AI controls into delivery workflows.
Define governance requirements for GenAI, agentic AI, copilots, traditional AI/ML, workflow automation, externally sourced AI tools, and vendor-delivered AI solutions.
Maintain enterprise AI inventory requirements, documentation standards, risk tiering, model/agent registry expectations, and evidence artifacts.
Establish requirements for human-in-the-loop controls, automation boundaries, transparency, traceability, explainability, bias review, data protection, and appropriate use.
Create governance standards for production readiness, observability, monitoring, incident response, issue escalation, policy exceptions, and ongoing control validation.
Support third-party AI and tool reviews by assessing responsible AI, data usage, model behavior, security, licensing, auditability, and control implications.
Develop practical guidance, templates, checklists, review criteria, and decision records that make governance usable by delivery teams.
Report governance status, control coverage, material risks, open issues, and decision needs to AI CoE and enterprise leadership forums.