VP, Enterprise Responsible AI and Data Quality Assurance Operations
Core
Lead the enterprise operating model and control plane for Responsible AI (RAI) and Data Quality (DQ) assurance, translating policy into actionable controls, automation, and measurable outcomes across business units and technology teams.
Role type
VP, Enterprise Responsible AI and Data Quality Assurance Operations
Builds
Centralized governance engine, enterprise-wide intake/risk-tiering workflows, policy-as-code patterns, and continuous monitoring for model performance, fairness, drift, and data observability.
Domain
Financial services, AI governance, data quality assurance, regulatory compliance
Deliverable
production ML models | dashboards & analysis | infrastructure
Required skills
AI governance and risk management, enterprise data quality governance, ModelOps/DataOps lifecycle management, cross-functional team leadership, regulatory compliance strategy, incident and exception management, stakeholder influence
Preferred skills
Advanced degree in computer science or related field, experience in complex global regulated environments
Technologies
ModelOps platforms, data observability tools, metadata management, lineage/provenance tracking, case management systems
Responsibilities
Establish and enforce enterprise RAI/DQ governance execution models and control planes; own centralized workflows and tooling for enterprise oversight; develop governance frameworks, standards, and audit-ready documentation; lead cross-enterprise governance rhythms and review boards; define and publish enterprise KPIs and dashboards for risk posture and compliance; lead the Data Quality Assurance function with top-down standards and independent assurance; integrate data quality controls into AI lifecycle governance gates; manage the RAI/DQ operations tooling roadmap; drive continuous improvement in automation and scalability of RAI/DQ operations.
Seniority
VP, strategic leadership with hands-on operational oversight
