Executive Director, AI Testing & Monitoring – HR & Employee Experience

Are you passionate about driving responsible AI innovation in a dynamic, people-focused environment? Join us to lead a new Center of Excellence dedicated to testing and monitoring AI solutions that support HR and Employee Experience. You will have the opportunity to shape the future of AI governance, collaborate with cross-functional teams, and make a meaningful impact on how we support our employees. This is your chance to champion ethical AI practices and deliver enterprise-grade solutions.

As an Executive Director, AI Testing & Monitoring – HR & Employee Experience in the HR & Employee Experience CDAO team, you will establish and lead a new Center of Excellence focused on ensuring the accuracy, fairness, security, and governance of all AI and ML systems supporting HR and Employee Experience. You will partner with internal and external stakeholders to design, operate, and continuously improve a centralized testing framework, delivering trustworthy and explainable AI solutions.

Job responsibilities:

• Establish and lead the AI Testing & Monitoring Center of Excellence for HR and Employee Experience, setting its mission, strategy, and success metrics.
• Serve as the accountable owner for model quality assurance and ethical compliance across all HR and Employee Experience AI use cases.
• Align testing standards with firmwide AI risk management and governance frameworks.
• Design and operationalize a dual-lane testing model for generative and statistical/ML AI solutions.
• Implement continuous monitoring pipelines and dashboards to detect model drift, data quality issues, and policy violations.
• Define and maintain standard metrics, SLAs, and certification thresholds for production readiness and operational health.
• Act as the primary executive interface for external vendors delivering testing capabilities, overseeing vendor performance, budget, and contract management.
• Ensure vendor alignment with security, privacy, and regulatory standards, and drive innovation through automated testing, synthetic data, and bias mitigation techniques.
• Partner with HR and Employee Experience product teams to embed testing checkpoints throughout the AI development lifecycle.
• Collaborate with Compliance, Legal, Model Risk, and Operational Risk teams to ensure traceability, auditability, and regulatory adherence.
• Deliver regular executive dashboards and readouts to HR leadership and governance committees, and champion a culture of responsible AI by educating stakeholders on best practices and ethical principles.

Required qualifications, capabilities, and skills:

• Minimum 10 years of experience in AI/ML governance, data science, or AI product leadership, with at least 5 years in a regulated enterprise environment and Advanced degree in Data Science, Statistics, Computer Science, or related discipline.
• Proven experience building or managing model testing or validation functions, ideally within financial services, technology, or consulting.
• Deep understanding of generative AI and large language model evaluation techniques, including prompt variance testing, bias audits, hallucination metrics, and guardrail evaluation.
• Strong grounding in statistical and predictive model validation, including drift analytics, bias detection, and performance monitoring.
• Exceptional cross-functional influence and vendor management skills.
• Demonstrated ability to translate technical risk concepts into business and ethical language for senior executives.

Preferred qualifications, capabilities, and skills:

• Experience with automated testing, synthetic data generation, and AI judging techniques.
• Familiarity with enterprise MLOps, data lineage, and cataloging systems.
• Strong understanding of HR and Employee Experience processes and technologies.
• Experience working with global teams and managing complex stakeholder relationships.
• Excellent communication and presentation skills.
• Track record of driving innovation in AI governance and risk management.
• Professional certifications in AI, data science, or risk management.