Director, AI Governance & Data Quality

Insight Global; Newark (NJ); On-site; USD 170,000 - 230,000; Full time

Job summary

Insight Global is seeking an IT Governance Director, Standards & Integrations to lead data quality and Responsible AI governance for Prudential. You will translate governance expectations into repeatable testing, monitoring, and remediation processes.

The role includes supporting intake and risk classification, conducting pre-release reviews, monitoring AI in production, and preparing audit-ready documentation, dashboards, and KPI/KRI reporting to show data quality and AI risk progress.

Qualifications

• 5+ years in data quality and data governance in regulated environments.
• Strong experience with Responsible AI control planes and ModelOps.
• Experience setting up AI tests, controls, and risk management processes.
• AWS AgentCore knowledge.
• Experience with AWS Bedrock and Microsoft Foundry Python coding.
• Experience in financial services or other highly regulated industries.
• Experience supporting global teams.

Responsibilities

• Translate governance expectations into repeatable testing, monitoring, reporting, and remediation processes.
• Support intake and risk classification, monitor AI in production, and manage exceptions.
• Prepare audit-ready documentation and evidence packages.
• Develop dashboards and KPI/KRI reporting to show data quality, AI risk, and remediation progress.

Skills

Data quality governance

Data profiling

Data lineage

Metadata management

AI governance

ModelOps

AI testing & controls

Risk management

AWS AgentCore

Regulated industries

Global collaboration

Continuous monitoring

Tools

AWS Bedrock

Microsoft Foundry Python

Job description

Insight Global is seeking an IT Governance Director, Standards & Integrations to lead data quality and Responsible AI governance for Prudential. You will translate governance expectations into repeatable testing, monitoring, and remediation processes.

The role includes supporting intake and risk classification, conducting pre-release reviews, monitoring AI in production, and preparing audit-ready documentation, dashboards, and KPI/KRI reporting to show data quality and AI risk progress.