VP, Enterprise Responsible AI and Data Quality Assurance Operations

Prudential Financial • Newark, NJ

1d • $178,600 - $267,800 • Hybrid

About The Position

As the Vice President, Enterprise Responsible AI (RAI) and Data Quality (DQ) Assurance Operations at Prudential Financial, you will lead the enterprise operating model and control plane for RAI and DQ—translating policy and standards into actionable controls, decision rights, automation, and measurable outcomes across business units and technology teams. In partnership with the VP, Responsible AI and QA Leader, you will establish centralized oversight mechanisms and ensure governance is executed in the flow of delivery across the AI and data lifecycles. In this global role, you will run the centralized governance engine for Responsible AI and Data Quality—defining enterprise-wide intake, risk-tiering, review, approval, and escalation workflows; setting expectations for documentation, testing, and monitoring; and implementing policy-as-code patterns where feasible to automate control checks and evidence capture across ModelOps/DataOps platforms. Your leadership will strengthen Prudential’s ability to scale AI safely by operationalizing continuous monitoring for model performance, fairness, drift, and stability—paired with modern data observability for completeness, accuracy, timeliness, and lineage. You will establish an enterprise issue, incident, and exception management approach (ownership, SLAs, remediation, and audit-ready evidence) and provide senior leaders transparent reporting on risk posture, control effectiveness, and compliance status. In essence, as VP of Enterprise RAI and DQ Assurance Operations, you will design and run Prudential’s end‑to‑end RAI/DQ operations and control plane—ensuring consistent enforcement of standards, measurable control coverage, and independent challenge so AI and data products are delivered in alignment with policy, risk appetite, and evolving regulatory expectations.

Requirements

• A minimum of 10 years of experience in a leadership role with a focus on AI governance, policy, risk management, ethics, or a related discipline, ideally within complex, global, and regulated environments.
• Strong understanding of AI/ML development lifecycles, model operations, and the technical processes required to support scalable AI delivery.
• Demonstrated leadership in enterprise data quality governance and assurance, including defining DQ standards/controls, overseeing testing and monitoring, and driving remediation across federated data owners.
• Working knowledge of data quality and data governance practices and tooling (DQ rules, metadata management, lineage, stewardship, MDM/reference data, and/or data observability) in regulated environments.
• Demonstrated experience operationalizing complex technical programs across large, federated organizations.
• Proven ability to lead cross‑functional teams and influence technical and non‑technical stakeholders.
• Exceptional communication, collaboration, and problem‑solving skills.

Nice To Haves

• Advanced degree in computer science, data science, applied mathematics, AI/ML, engineering, or a related field preferred.

Responsibilities

• Establish and enforce an enterprise Responsible AI and Data Quality governance execution model and control plane (controls, decision rights, operating cadence, control testing, and issue/exception management), in coordination with the VP, RAI Governance & Policy.
• Own the centralized workflows, tooling, and integrations required for enterprise oversight—enabling model and use-case inventory, control mapping, required evidence capture, attestations, and continuous monitoring (leveraging ModelOps and adjacent platforms).
• Develop and maintain governance frameworks, mandatory standards, control libraries, playbooks, templates, and audit-ready documentation that teams must follow to meet Responsible AI and Data Quality requirements efficiently—embedding controls into delivery through repeatable patterns and guidance.
• Lead cross‑enterprise governance rhythms (intake, risk-tiering, review boards, control gates, independent challenge, and escalation) to drive consistent adoption of RAI and DQ controls across business, technology, and analytics teams.
• Define and publish enterprise KPIs and dashboards spanning compliance, risk posture, control coverage/effectiveness, exceptions, incidents, and remediation progress; deliver actionable reporting to senior stakeholders and governance forums.
• Lead the enterprise Data Quality Assurance (DQA) function by defining and running top‑down quality standards and controls for critical data (including critical data elements) and executing independent assurance (rules-based testing, sampling, and challenge) supported by modern data observability and lineage/provenance.
• Establish enterprise DQ monitoring and issue/incident management with clear ownership, SLAs, escalation paths, root-cause analysis expectations, and audit-ready evidence of detection, triage, remediation, and validation.
• Integrate data quality controls into AI lifecycle governance gates (intake, validation, deployment, and monitoring) to ensure models rely on fit‑for‑purpose data and features—with documented lineage, provenance, label/ground-truth quality where applicable, and defined acceptance criteria for data fitness.
• Manage the RAI/DQ operations tooling roadmap with product and engineering partners—driving integration across model registries, evaluation frameworks, monitoring/observability, metadata and lineage, case management, and reporting to support scalable control-plane execution.
• Build and lead role-based training and enablement that empowers teams to execute RAI and DQ practices effectively—focusing on practitioner playbooks, templates, office hours, and hands‑on support.
• Stay current on emerging tools, methods, and regulatory expectations (including GenAI/LLM evaluation, monitoring, and documentation patterns) and integrate improvements into Prudential’s operational model and control plane.
• Drive continuous improvement to raise the maturity, automation, and scalability of RAI/DQ operations—reducing delivery friction while strengthening control effectiveness and audit readiness.
• Develop strong relationships with business, technology, risk, compliance, and legal partners—ensuring shared understanding of requirements, clear ownership, and a compelling value proposition for RAI and DQ controls.
• Represent the RAI/DQ Operations control plane in cross‑enterprise forums, ensuring alignment across stakeholders involved in AI and data delivery and consistent execution of governance decisions.

Benefits

• Market competitive base salaries, with a yearly bonus potential at every level.
• Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave.
• 401(k) plan with company match (up to 4%).
• Company-funded pension plan.
• Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.
• Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development.
• Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs.
• Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period), after one year of service.
• Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive