AI Risk and Governance Lead

Location: Remote: Eastern or Central Time Zone location preferred
Employment Status: Salary Full-Time
Function: Information Technology
Pay Grade and Range: AFY000-P4 ($112,000 - $140,000)
Bonus Plan: AIP
Target Bonus: 15.0
Recruiter: Allison SchockReq ID: 30004

Position Summary

The AI Risk and Governance Lead is responsible for establishing, implementing, and overseeing the organization's AI governance framework, ensuring artificial intelligence solutions are deployed responsibly, ethically, securely, and in compliance with applicable laws, regulations, and company policies.

This role serves as the critical bridge between Legal, Enterprise Risk Management (ERM), Cybersecurity, Privacy, Internal Audit, Technology, Data Science, and Business teams to ensure AI solutions align with enterprise risk tolerance and regulatory expectations.

The AI Risk and Governance Lead translates emerging AI regulations, ethical principles, and risk requirements into practical, scalable guardrails that enable responsible innovation rather than create barriers to business value. The role will establish governance processes, operationalize regulatory requirements, and ensure AI risks are proactively identified, assessed, monitored, and managed throughout the AI lifecycle.

Primary Responsibility

Serve as the enterprise lead for AI Risk and Governance by translating evolving AI regulations, risk management frameworks, and responsible AI principles into practical governance controls, standards, and operating procedures that enable safe, compliant, and scalable AI adoption across the organization.

Key Responsibilities

AI Governance Strategy

• Develop and maintain the enterprise AI governance framework, policies, standards, and operating model.
• Establish governance processes across the AI lifecycle, including development, acquisition, deployment, monitoring, and retirement.
• Lead governance committees and facilitate executive-level discussions regarding AI opportunities, risks, and compliance obligations.
• Define roles, responsibilities, decision rights, and accountability mechanisms for AI oversight.

Regulatory and Framework Operationalization

• Operationalize emerging AI regulations and industry-leading frameworks, including:
  • EU AI Act
  • NIST AI Risk Management Framework (AI RMF)
  • Responsible AI and industry best practices
• Translate regulatory and ethical requirements into practical controls, standards, review processes, and implementation guidance.
• Monitor emerging AI legislation, regulatory developments, and enforcement activities and assess organizational impacts.

Key Responsibilities (Continued)

AI Risk Management

• Design and implement enterprise AI risk assessment methodologies and governance controls.
• Lead AI risk assessments with a particular focus on high-risk, regulated, customer-facing, and business-critical use cases.
• Identify, assess, mitigate, and monitor risks including:
  • Bias and fairness risks
  • Privacy and data protection risks
  • Cybersecurity risks
  • Intellectual property and copyright risks
  • Regulatory compliance risks
  • Model performance and reliability risks
  • Reputational risks
  • Third-party and vendor risks
• Develop and maintain an enterprise AI risk tiering model to classify use cases and determine governance requirements based on risk exposure.
• Maintain inventories of AI systems, models, and use cases.

Key Responsibilities (Continued)

Responsible AI and Controls

• Establish standards and procedures for:
  • Human-in-the-loop review and oversight
  • Transparency and explainability
  • Bias testing and fairness assessments
  • Model monitoring and drift detection
  • Data retention and governance
  • Intellectual property protection
  • AI incident management and escalation
  • Ongoing performance monitoring and validation
• Ensure responsible AI principles are embedded into AI design, development, deployment, and monitoring activities.
• Review and challenge high-risk AI use cases and provide governance recommendations.

Vendor AI Governance

• Evaluate third-party AI solutions, vendor-provided AI capabilities, and embedded AI tools through a risk, compliance, privacy, cybersecurity, and legal lens.
• Establish AI vendor due diligence, assessment, and monitoring procedures.
• Partner with Procurement, Legal, Security, and Privacy teams to assess risks associated with external AI technologies and suppliers.

Key Responsibilities (Continued)

Cross-Functional Collaboration

• Serve as the primary liaison across Legal, ERM, Cybersecurity, Privacy, Internal Audit, Technology, Data Science, and Business functions.
• Partner with stakeholders to integrate AI governance requirements into existing risk and control frameworks.
• Advise business leaders and project teams on AI-related risks, regulatory obligations, and governance requirements.
• Promote risk-informed decision-making while enabling innovation and business outcomes.

Assurance, Audit, and Compliance

• Partner with Enterprise Risk Management and Internal Audit to establish AI assurance processes and governance reviews.
• Support internal and external audits of AI controls and governance programs.
• Develop control testing, monitoring, and remediation processes to assess governance effectiveness.
• Track and oversee remediation of identified AI-related risks and control gaps.

Key Responsibilities (Continued)

Monitoring, Reporting, and Metrics

• Develop key performance indicators (KPIs), key risk indicators (KRIs), dashboards, and governance reporting.
• Provide regular updates to executive leadership, governance committees, and risk oversight bodies.
• Monitor compliance with AI governance standards and risk management requirements.

Training and Change Management

• Develop and deliver AI governance, responsible AI, and risk awareness programs.
• Foster a culture that balances innovation with accountability and regulatory compliance.
• Drive adoption of governance processes and responsible AI practices across the enterprise.

Required Qualifications

• Bachelor's degree in Risk Management, Business, Computer Science, Information Technology, Data Science, Cybersecurity, Law, or a related field.
• 8+ years of experience in risk management, governance, compliance, audit, cybersecurity, privacy, data governance, or related disciplines.
• 3+ years of experience supporting AI, machine learning, advanced analytics, or emerging technology governance programs.
• Experience designing and implementing enterprise governance frameworks and operating models.
• Demonstrated knowledge of:
  • AI and machine learning concepts
  • Responsible AI principles
  • Enterprise Risk Management practices
  • Privacy and data protection requirements
  • Cybersecurity controls
  • Model governance and model risk management
  • AI regulations and governance frameworks (including EU AI Act and NIST AI RMF)
• Strong executive communication, influence, and stakeholder management skills.
• Ability to travel regionally as needed 5% of the time

Lincoln Electric is an Equal Opportunity Employer. We are committed to promoting equal employment opportunity for applicants, without regard to their race, color, national origin, religion, sex (including pregnancy, childbirth, or related medical conditions, including, but not limited to, lactation), sexual orientation, gender identity, age, veteran status, disability, genetic information, and any other category protected by federal, state, or local law.