AI Governance Lead - Hybrid Boston or Webster

Date:
Oct 27, 2026

Location:

Webster, MA, US

Company: MAPFRE

Summary

Mapfre is seeking a Responsible AI Governance Lead, who combines hands‑on AI expertise with the judgment to enable responsible innovation in insurance, to help shape how ML, GenAI, and Agentic AI solutions are designed, evaluated, and deployed responsibly. Working alongside data scientists, AI engineers, and business teams throughout the AI lifecycle, you will apply hands‑on technical expertise to challenge solution designs, test model and agent behavior, and embed practical controls.

This role will help lead the operation and continuous improvement of Mapfre’s AIS Governance program, enabling responsible adoption of AI across the organization. You will maintain the enterprise AI inventory, lead risk assessments, coordinate approvals, and oversee ongoing risks across AI tools, platforms, and use cases. Partnering with Legal, Compliance, Information Security, and Risk, you will ensure governance decisions are supported by technical evidence and maintain regulatory readiness.

As a key leader in Mapfre's Data & AI Governance organization, you will help shape the organization's AI governance strategy while enabling innovation through practical, scalable governance practices that balance opportunity, risk, compliance, and business value.

Strong knowledge of insurance operations and regulatory expectations is required.

What You'll Do

• AI Governance
  
  Program: Lead the operation and continuous improvement of Mapfre’s AIS Governance Program, including its operating model, accountability structures, decision forums, standards, and alignment with enterprise strategy and risk appetite.
• AI Inventory & Lifecycle Governance: Maintain and improve an enterprise AI inventory covering tools, platforms, use cases, data products, models, systems, vendors and agents, during their lifecycle. Own requirements for supporting governance workflows and evidence repositories, ensuring appropriate documentation, ownership, approvals, traceability, and risk assessments.
• Responsible AI Policies & Controls: Develop and maintain Responsible AI policies, standards, procedures, assessment frameworks, and control requirements covering fairness, explainability, transparency, human oversight, privacy, security, robustness, and accountability, in partnership with the relevant control functions.
• AI Risk, Approvals and Regulatory readiness: Partner with Risk, Compliance, Legal, Privacy, Security, Audit, and Architecture teams to assess and coordinate governance reviews, risks and approval decisions for AI tools, platforms and use cases; define permitted uses and required controls; verify mitigation evidence; and track approval conditions. Coordinate documentation and technical explanations for DOI inquiries and examinations with Legal and Compliance.
• AI Technical Assurance & Delivery Partnership: Collaborate with data, AI, architecture, security, and delivery teams to review AI solution design, development, implementation and operation to shape evaluation approached and embed Responsible AI controls. Challenge technical evidence, reproduce key metrics, and conduct targeted testing where needed, including assessment of agent permissions, autonomy, and human oversight. Define monitoring requirements with model and platform owners, review results and incidents, and track remediation, reassessment, and escalation of material risks.
• Education, Awareness & Enablement: Build Responsible AI knowledge through practical and targeted guidance, training, communications, reusable assessment templates/tools , and governance forums, while serving as a trusted advisor to business and technology stakeholders.
• Innovation & Continuous…