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Global Payments Inc. · 18 hours ago

AI Governance Technology Lead

Atlanta, GA

Full-time

Onsite

Senior Level, Lead/Staff

5+ years exp

Global Payments Inc. is seeking a Principal, AI Testing & Monitoring who will be responsible for validating and continuously monitoring AI/ML models to ensure compliance with enterprise standards. The role involves designing validation protocols, deploying monitoring capabilities, and working with various teams to assess AI model performance and ensure adherence to ethical AI principles.

AppsBankingCreditEnterpriseFinanceFinancial ServicesPayments

Responsibilities

Lead the design, development, and execution of independent AI/ML model validation frameworks across various use cases

Conduct bias audits, adversarial testing, and stress testing to evaluate model robustness, fairness, and resilience against vulnerabilities

Apply statistical testing, benchmarking methodologies, and explainability (XAI) techniques to ensure models are transparent and interpretable

Utilize synthetic data generation and automated testing frameworks to simulate edge cases and rare scenarios for risk assessment

Document validation methodologies, findings, and risk-based recommendations for stakeholders, ensuring traceability and audit-readiness

Develop and implement enterprise AI monitoring frameworks for deployed models, focusing on real-time performance tracking, bias detection, and compliance verification

Apply anomaly detection and AI observability solutions to identify and remediate performance degradation, drift, or ethical risks

Oversee incident response for AI failures, coordinating with risk, compliance, and engineering teams to ensure timely mitigation

Integrate monitoring insights into governance dashboards and reporting platforms to inform executives and regulatory stakeholders

Ensure all testing and monitoring activities align with RUAI principles, industry best practices, and applicable regulations (e.g., EU AI Act, GDPR, CCPA, Colorado AI Act, NIST AI RMF)

Leverage AI governance platforms and risk assessment tools to centralize validation evidence, compliance records, and ongoing monitoring metrics

Partner with Legal, Compliance, and Risk to interpret regulatory requirements and translate them into actionable technical and operational controls

Provide expert guidance to data scientists and engineers on bias mitigation, fairness optimization, and explainability best practices

Stay informed on emerging trends in AI risk assessment, validation methodologies, monitoring tools, and regulatory developments

Lead workshops, training sessions, and cross-functional knowledge sharing to advance organizational maturity in AI testing and monitoring

Contribute to enterprise AI governance strategy by identifying technology investments, process enhancements, and automation opportunities

Provides guidance and mentoring to analysts, as needed

Not an exhaustive list; other duties as assigned

Qualification

AI/ML model validationAI governance principlesBias auditsAnomaly detectionStatistical testingExplainability techniquesMonitoring frameworksRisk managementAnalytical skillsCommunication skillsProblem-solving skillsTeam collaboration

Required

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Information Systems, or related field

5+ years in independent AI/ML model testing and validation, including robustness, fairness, and compliance verification

3–5+ years in AI monitoring and risk management, including real-time model performance tracking, anomaly detection, and compliance monitoring

Proven experience developing and executing rigorous validation frameworks and performing bias, adversarial, and stress testing

Strong knowledge of AI governance principles, ethical AI frameworks, and relevant regulations (EU AI Act, GDPR, CCPA, Colorado AI Act, NIST AI RMF)

Hands-on experience with validation tools, statistical testing frameworks, synthetic data generation, automated testing platforms, and AI observability tools

Deep expertise in model validation, fairness audits, and explainability techniques

Proficiency in monitoring and logging frameworks for AI/ML systems

Strong analytical and problem-solving skills with the ability to identify risks and propose actionable mitigations

Excellent written and verbal communication skills to document findings, influence stakeholders, and present to executive leadership

Ability to work across diverse teams and translate complex technical concepts into clear operational and compliance guidance

Preferred

Master's Degree

Typically, Masters in Business Administration, Computer Science, Information Management, Quantitative Analytics, Data Science, or similar discipline

Experience establishing AI Governance programs, specifically processes, procedures, and frameworks for AI model testing and validation, AI solution monitoring, and AI risk management