Responsible AI Governance Lead - Hybrid Boston or Webster

MAPFRE•Webster, MA

2d•$121,100 - $182,000•Hybrid

About The Position

Mapfre is seeking a Responsible AI Governance Lead to combine hands-on AI expertise with sound judgment in support of responsible innovation across insurance. The role partners with data scientists, AI engineers, and business teams throughout the AI lifecycle to review solution designs, test model and agent behavior, and embed practical controls for machine learning, generative AI, and agentic AI. The Lead operates and continuously improves Mapfre’s AI Governance Program, maintains the enterprise AI inventory, leads risk assessments, coordinates approvals, and oversees ongoing risks across AI tools, platforms, and use cases. In partnership with Legal, Compliance, Information Security, Risk, and other functions, the role supports technically grounded governance decisions and regulatory readiness. It also contributes to AI governance strategy and scalable practices that balance opportunity, risk, compliance, and business value. Strong knowledge of insurance operations and regulatory expectations is required.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Mathematics, Data Science, Engineering, Analytics, or a related field.
12 or more years of experience, including substantial hands-on Data Science or AI experience and at least 4 years in Data & AI Governance, model validation, risk management, or technical AI assurance.
Strong understanding and hands-on experience in Machine Learning, Generative AI, AI Agents, LLMs, model lifecycle management, and AI delivery practices.
Proficiency in Python and SQL, with the ability to reproduce and interpret model performance, fairness, and explainability assessments and conduct targeted technical testing.
Ability to review and constructively challenge AI architecture, MLOps, cloud platforms, APIs, security, and data management, including agent tool use, retrieval, identity, permissions, autonomy, and human oversight.
Experience developing governance frameworks, policies, standards, operating models, or enterprise programs, including AI inventories, risk assessments, approval workflows, control evidence, and remediation tracking.
Experience working with cross-functional teams including Business, Technology, Security, Risk, Compliance, Legal, and Data Science/AI organizations.
Ability to translate regulatory and policy requirements into practical AI controls, assessment criteria, and defensible documentation while working with Legal and Compliance.
Strong project management and prioritization skills, including demonstrated ability to coordinate cross-functional reviews and drive decisions, approval conditions, and remediation to completion.
Strong communication, stakeholder management, facilitation, and influence skills.
Experience translating technical concepts into practical business guidance and governance requirements.
Strong understanding of data governance, privacy, security, and risk management principles.
Ability to engage technical teams in discussions involving AI architecture, MLOps, cloud platforms, APIs, security, and data management.
Experience with Microsoft Copilot, Copilot Studio, Azure AI Services, OpenAI, AWS AI, SageMaker, Databricks, Snowflake AI, or similar platforms.
Property & Casualty insurance industry knowledge.

Nice To Haves

Experience establishing or operating an AI Governance, Responsible AI, Model Risk Management, or AI Compliance program.
Experience supporting AI inventories, AI use case assessments, model governance, or AI risk management processes.
Familiarity with Responsible AI frameworks such as NIST AI RMF, ISO 42001, OECD AI Principles, or similar industry frameworks.
Experience working with AI lifecycle platforms, model registries, governance tools, or AI observability solutions.
Familiarity with privacy, security, and regulatory requirements impacting AI solutions.
Experience supporting AI governance committees, review boards, or executive governance forums.
Professional certifications in AI, Data Governance, Risk Management, Security, or Project Management.

Responsibilities

Lead the operation and continuous improvement of Mapfre’s AI Governance Program, including its operating model, accountability structures, decision forums, standards, and alignment with enterprise strategy and risk appetite.
Maintain and improve an enterprise AI inventory covering tools, platforms, use cases, data products, models, systems, vendors, and agents throughout their lifecycle.
Own requirements for governance workflows and evidence repositories, ensuring appropriate documentation, ownership, approvals, traceability, and risk assessments.
Develop and maintain Responsible AI policies, standards, procedures, assessment frameworks, and control requirements covering fairness, explainability, transparency, human oversight, privacy, security, robustness, and accountability.
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.
Collaborate with data, AI, architecture, security, and delivery teams to review AI solution design, development, implementation, and operation; shape evaluation approaches 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.
Build Responsible AI knowledge through practical guidance, training, communications, reusable assessment templates and tools, and governance forums; serve as a trusted advisor to business and technology stakeholders.
Evaluate emerging AI governance frameworks, technologies, standards, and regulations; recommend improvements; and support Mapfre’s long-term AI maturity and governance roadmap.