VP, Enterprise AI and Data Quality Assurance Operations

Position: VP, Enterprise Responsible AI and Data Quality Assurance Operations
Job Classification:

Technology - Data Analytics & Management

Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability, and efficiency? The Global Technology team takes great pride in our culture where digital transformation is built into our DNA! When you join our organization at Prudential, you'll unlock an exciting and impactful career - all while growing your skills and advancing your profession at one of the world's leading financial services institutions.

Your Team

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 life cycles.

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 Model Ops/Data Ops 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.

Location:

Newark, NJ hybrid (minimum 3 days/week in office)

Here is What You Can Expect on a Typical Day

* 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 Model Ops 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…