Governance, Risk and Compliance (GRC) AI Lead

Worldwide Clinical Trials•Durham, NC

1d•$101,000 - $201,000•Remote

About The Position

The Governance, Risk and Compliance (GRC) AI Lead will shape how AI is governed across Worldwide Clinical Trials by building and leading the Enterprise IT AI Governance framework. The role establishes practical, risk-based processes for AI systems, AI-enabled technologies, and AI agents throughout their lifecycle—from use-case evaluation and approval through ongoing monitoring and retirement—to support secure, responsible adoption aligned with regulatory, contractual, and business requirements. This is a collaborative role partnering with business owners and specialists across Information Security, Privacy, Legal, Quality, Enterprise Architecture, Data, Vendor Management, and Procurement. The position brings these perspectives together, maintains clear accountability, and enables teams to pursue AI opportunities with appropriate controls and human oversight. The role is remote and open to candidates based in the United States, with collaboration across global teams and time zones. The stated annual salary range is $101,000 to $201,000. A competitive benefits package is offered, with details depending on location.

Requirements

Bachelor's degree in Information Technology, Cybersecurity, Computer Science, Data Science, Risk Management, Business, Law, or a related field.
At least 8 years of progressive experience in governance, risk and compliance, technology risk, cybersecurity, privacy, data governance, audit, quality, or a related discipline.
At least 3 years leading enterprise governance programs, cross-functional risk initiatives, or technology control frameworks.
Demonstrated experience developing policies, standards, risk assessments, control requirements, governance workflows, metrics, and executive reporting.
Strong understanding of technology risk, information security, privacy, third-party risk, data governance, and regulatory compliance.
Practical knowledge of large language models, AI agents, machine identities, and AI lifecycle risks.
Strong program-management, stakeholder-management, and communication skills, including the ability to translate complex legal, regulatory, security, privacy, quality, and business requirements into practical controls and communicate risk to technical and nontechnical audiences.
Proficiency in English and ability to collaborate across global time zones and manage multiple governance priorities.

Nice To Haves

An advanced degree.
Working experience with AI governance, responsible AI, generative AI, machine learning, automation, AI-enabled vendor products, or AI agent governance.
Experience in a regulated, global, life sciences, healthcare, or clinical research environment.
Familiarity with recognized AI, risk, security, and privacy frameworks and applicable AI laws and regulations.

Responsibilities

Build and maintain the Enterprise IT AI Governance framework, including its operating model, standards, procedures, decision rights, risk tiers, controls, and governance records.
Establish a company-wide intake, assessment, and approval process for AI use cases, AI-enabled vendor products, internally developed solutions, and AI agents.
Maintain a centralized inventory of AI systems and agents, including ownership, intended use, data sources, permissions, dependencies, risk classification, approval status, and lifecycle information.
Lead risk-based governance reviews in partnership with Information Security, Privacy, Legal, Quality, Enterprise Architecture, Data, Vendor Management, Procurement, and other subject-matter experts.
Define governance requirements for AI agents, including ownership, approved purpose, identity and access, human oversight, testing, monitoring, logging, change control, incident response, and secure retirement.
Coordinate reviews of cybersecurity, privacy, quality, third-party, and operational risks associated with AI, including sensitive data exposure, prompt injection, excessive agency, insecure integrations, identity misuse, unauthorized actions, and supply-chain dependencies.
Strengthen governance for clinical, GxP, and other regulated AI use cases in partnership with Quality and business owners, covering validation, human oversight, data integrity, change control, recordkeeping, and inspection readiness.
Monitor approved AI technologies for material changes, control exceptions, incidents, performance concerns, and emerging requirements, and trigger reassessment and remediation when appropriate.
Deliver practical governance guidance, training, metrics, executive reporting, and audit-ready evidence.
Advise leadership on emerging AI risks, governance gaps, and investment needs.