Principal, AI Governance and Tooling at Global Payments

Alpharetta, Georgia, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

FinTech, Payments, Financial ServicesIndustries

Requirements

Senior technical expertise in AI/ML model validation, governance, and monitoring
Deep knowledge of AI robustness, fairness, transparency, compliance, and ethical principles
Proficiency in statistical testing, benchmarking, explainability (XAI) techniques, bias audits, adversarial testing, and stress testing
Experience with synthetic data generation, automated testing frameworks, anomaly detection, and AI observability solutions
Familiarity with AI governance platforms, risk assessment tools, and monitoring frameworks
Understanding of regulations and standards (e.g., EU AI Act, GDPR, CCPA, Colorado AI Act, NIST AI RMF)
Ability to interpret regulatory requirements and translate them into technical/operational controls
Knowledge of emerging trends in AI risk assessment, validation, monitoring tools, and regulatory developments
Strong collaboration skills with Data Science, Engineering, Legal, Compliance, Risk, and IT teams
Capability to provide expert guidance, mentoring, lead workshops/training, and contribute to strategy

Responsibilities

Lead the design, development, and execution of independent AI/ML model validation frameworks across use cases
Conduct bias audits, adversarial testing, and stress testing to evaluate model robustness, fairness, and resilience
Apply statistical testing, benchmarking, and XAI techniques for model transparency and interpretability
Utilize synthetic data and automated frameworks to simulate edge cases for risk assessment
Document validation methodologies, findings, and recommendations for stakeholders, ensuring audit-readiness
Develop and implement enterprise AI monitoring frameworks for real-time performance, bias detection, and compliance
Apply anomaly detection to identify and remediate performance degradation, drift, or ethical risks
Oversee incident response for AI failures, coordinating with relevant teams for mitigation
Integrate monitoring insights into governance dashboards and reporting for executives and regulators
Ensure alignment with RUAI principles, best practices, and regulations
Leverage AI governance platforms to centralize validation evidence, compliance records, and metrics
Partner with Legal, Compliance, and Risk to implement controls
Provide guidance to data scientists and engineers on bias mitigation, fairness, and explainability
Stay informed on trends and lead workshops/training for organizational maturity
Contribute to AI governance strategy, identifying investments, enhancements, and automation opportunities
Provide guidance and mentoring to team members

Skills

Key technologies and capabilities for this role

AI/ML Model ValidationBias AuditsAdversarial TestingStress TestingFairness EvaluationExplainability TechniquesAI GovernanceStatistical AnalysisModel MonitoringRisk Assessment

Questions & Answers

Common questions about this position

What is the employment type for this role?

This is a full-time position.

What are the main responsibilities of the Principal, AI Governance and Tooling role?

The role involves leading AI/ML model validation frameworks, conducting bias audits and testing, developing monitoring frameworks, and ensuring compliance with AI governance standards while collaborating with cross-functional teams.

What technical skills are required for this position?

Key skills include expertise in AI/ML model validation, bias audits, adversarial and stress testing, statistical testing, explainability (XAI) techniques, anomaly detection, and AI observability solutions.

What teams will I work with in this role?

You will work closely with Data Science, Engineering, Legal, Compliance, Risk, and IT teams.

What makes a strong candidate for this Principal role?

A strong candidate has senior-level expertise as a technical authority in AI model reliability, security, governance, and risk management, with the ability to design validation protocols, implement monitoring, and provide recommendations to leadership.