AI Vendor Governance Manager

Omnicell•Atlanta, GA

1d•Hybrid

About The Position

Omnicell is building its AI governance program and is looking for a Manager, AI Vendor Governance to join its Legal Department. This role will own how AI enters the company through third parties. As a foundational member of Omnicell’s AI Governance Program, the individual will design and operate a third-party intake process that identifies AI solutions entering the organization, evaluates them against the company’s responsible-AI and risk standards, and determines the level of risk each presents to the business. Working closely with Procurement, Legal, Privacy, Security, Quality, and business owners, the role will establish questionnaires, risk-tiering criteria, and review workflows that allow Omnicell to adopt AI tools quickly and responsibly.

Requirements

6+ years of experience in third-party or vendor risk management, IT or security risk, compliance, or a related governance function
Demonstrated experience building or substantially maturing a vendor risk or governance program, including intake and risk-tiering processes
Strong knowledge of third-party and vendor risk management principles and lifecycle, from intake and due diligence through monitoring and offboarding
Familiarity with AI and machine learning concepts and the risks they raise, including bias, transparency, data privacy, security, and model reliability
Working knowledge of AI governance frameworks and standards, such as the NIST AI Risk Management Framework, ISO/IEC 42001, and the EU AI Act
Familiarity with security and privacy frameworks commonly used in vendor assessments, such as SOC 2, ISO 27001, HIPAA, and GDPR
A talent for designing clear, repeatable processes and operationalizing them across a cross-functional organization
The ability to assess complex risk and make pragmatic, risk-calibrated recommendations that balance innovation with protection of the business
A track record of partnering across Procurement, Legal, Privacy, Security, and business owners, with excellent stakeholder management skills
The ability to explain technical and risk concepts clearly to both technical and non-technical audiences
The ability to operate independently in a fast-moving environment, manage competing priorities, and stay highly organized, with sharp attention to detail and a commitment to thorough documentation

Nice To Haves

Bachelor’s degree, or equivalent practical experience
Experience assessing AI or machine learning solutions, or building AI-specific risk controls
Healthcare, life sciences, or other regulated-industry experience
Relevant certifications, such as AIGP, CIPP, CIPM, CTPRP, CRISC, CISA, or CISSP
Experience with third-party risk, GRC, or AI governance tooling, such as ServiceNow, OneTrust, or similar platforms
Familiarity with AI assurance artifacts, such as model cards, system cards, and impact assessments, and with vendor monitoring tools
Relevant advanced education, such as a degree or coursework in law, risk management, information security, data science, or a related field, or equivalent experience

Responsibilities

Give Omnicell a clear, defensible view of every AI solution entering the business through a third party, so that teams can adopt AI tools quickly and with confidence, and so that customers, regulators, and patients can trust how those tools are vetted and governed.
Build, implement, and mature Omnicell’s AI vendor governance program, including its policies, standards, intake process, and review workflows.
Design and operate a third-party intake process that identifies AI solutions entering the organization, including AI embedded within broader products and services, and routes them for risk review.
Develop risk-tiering and classification criteria that account for the AI use case, the sensitivity of the data involved, and the potential business impact of failure, bias, or misuse.
Create and maintain AI-specific due diligence questionnaires and assessment criteria covering model design, training data, transparency and explainability, bias mitigation, security, and ongoing monitoring.
Evaluate vendor documentation and control evidence, such as SOC 2 reports, ISO/IEC 42001 certifications, model cards, and impact assessments, and identify gaps that require remediation or compensating controls.
Determine and communicate the level of risk each AI solution presents, and partner with business owners on remediation, risk acceptance, or alternative approaches.
Maintain an inventory of third-party AI in use across the organization, working to surface and govern shadow AI.
Partner with Procurement and Legal to define contractual requirements for AI vendors, including disclosure of AI use, data handling, and responsible-AI commitments.
Establish continuous monitoring and periodic reassessment of AI vendors across the relationship lifecycle, from onboarding through offboarding.
Develop program metrics, reporting, and dashboards that demonstrate coverage, maturity, and risk posture to leadership, and track evolving AI regulations and standards, such as the EU AI Act and the NIST AI Risk Management Framework, that affect third-party AI.