VP Head of Global AI Architecture Governance

Chubb is a world leader in insurance. With operations in 54 countries Chubb provides commercial and personal property and casualty insurance personal accident and supplemental health insurance reinsurance and life insurance to a diverse group of clients. The company is distinguished by its extensive product and service offerings broad distribution capabilities exceptional financial strength underwriting excellence superior claims handling expertise and local operations globally.

Key Objectives:
Reporting to the SVP AI Engineering as the VP Head of Global AI Architecture & Governance you will play a key role in shaping the future of AI within Chubb. You will spearhead the development and implementation of robust AI architecture and governance frameworks policies and standards that ensure the compliant use of AI technologies across the company. In this position you will oversee various facets of the AI operating model including managing the AI capabilities inventory supervising AI risk tiering and establishing guidelines for production use.

Your collaboration will extend across crossfunctional teams including business stakeholders architects engineers legal and compliance professionals to advance AI governance initiatives to meet regulatory requirements and uphold industry best practices. Additionally you will lead efforts in coordinating AI risk assessments supporting generative AI proofofconcepts and actively participating in governance meetings.

This role is essential in fostering a culture of responsible AI use ensuring that our AI governance processes are effectively communicated and integrated into Chubbs overall risk framework. It presents a unique opportunity for a motivated individual to deepen their expertise in AI governance and operational models areas that are increasingly vital in the financial sector and broader economy. Additionally this role will enhance your expertise in AI technology and its significant impact on business operations and regulatory compliance.


Major Responsibilities:

• Strategic Leadership: Develop and execute a global AI architecture strategy aligned with business objectives ensuring the scalability reliability and security of AI systems and solutions.
• Governance Frameworks: Establish and maintain comprehensive AI governance policies standards and procedures that govern all AI initiatives while ensuring adherence to regulatory requirements and ethical standards.
• Operational Oversight: Oversee the operational implementation of AI projects across various teams ensuring that AI solutions are deployed effectively and meet required standards for performance and compliance.
• CrossFunctional Collaboration: Partner with business stakeholders risk management legal and compliance teams to ensure a holistic approach to AI governance. Facilitate crossdepartmental collaboration to align on best practices and standards.
• Model Management: Oversee the AI/ML model lifecycle to ensure effective model risk management including the development validation monitoring and reporting of AI models.
• Risk Assessment: Identify and assess risks associated with AI operations including issues of bias transparency and data governance implementing mitigative measures as necessary.
• Stakeholder Engagement: Communicate AI governance policies and operational strategies to diverse stakeholders fostering a culture of responsible AI adoption across the organization.
• Monitoring & Reporting: Implement continuous monitoring protocols for AI deployments ensuring compliance with governance policies and conducting regular audits to assess adherence to established standards.
• Innovation & Research: Stay abreast of industry trends regulatory changes and emerging technologies related to AI governance and operations propelling innovative solutions that enhance organizational capabilities.

Qualifications:

• Bachelors degree in computer science or a related STEM field is required.
• Masters degree in computer science Law Finance Business Administration or a related discipline is preferred.
• 12 years of industry experience with in 5 years of experience in AI/ML governance architecture or operations within a regulated industry such as financial services or insurance.
• Proven track record in developing and implementing AI governance frameworks policies and operational processes.
• Strong understanding of the regulatory landscape governing AI applications including data privacy bias prevention and ethical AI principles.
• Experience in risk management related to AI deployments and familiarity with relevant frameworks (e.g. NIST AI Framework GDPR).
• Exceptional analytical and problemsolving skills with a proven ability to address complex challenges in dynamic environments.
• Excellent communication presentation and interpersonal skills with the ability to influence and engage stakeholders at all levels.

Architecture Skills:

• Cloud Architecture Expertise: Proficiency in designing and implementing AI solutions on cloud platforms (e.g. AWS Azure Google Cloud) and understanding their infrastructure.
• Data Architecture: Understanding of data modeling data warehousing and data integration techniques to support AI initiatives.
• AI/ML Frameworks and Tools: Familiarity with popular machine learning frameworks (e.g. TensorFlow PyTorch Scikitlearn) and tools for AI model development and deployment.
• API Design and Integration: Skills in designing APIs to facilitate integration between AI systems and other enterprise applications.
• Cybersecurity Knowledge: Awareness of security challenges in AI systems and familiarity with security best practices ensuring data privacy and compliance.
• Performance Optimization: Ability to assess and improve the performance scalability and reliability of AI systems.
• Technology Roadmaps: Experience in developing and maintaining technology roadmaps that align with business and IT strategies.
• Change Management: Skills in managing change within the organization particularly related to the adoption of AI technologies.

Governance Skills:

• Regulatory Compliance and Risk Management: Deep understanding of compliance requirements data governance and legal considerations surrounding AI usage.
• CostBenefit Analysis: Ability to perform financial assessments of AI initiatives ensuring they provide value and align with business goals.
• Understanding of Responsible AI: Knowledge of principles and frameworks that promote fairness accountability and transparency in AI systems.
• Experience in Interdisciplinary Collaboration: Ability to facilitate cooperation among diverse disciplines such as data science ethics and business operations to create holistic AI solutions.
• Relevant certifications in AI governance data governance or risk management (CISSP CISA CRISC) are highly desirable.

At Chubb we are committed to providing equal employment opportunities to all employees and applicants. It is our policy to provide equal employment opportunities to employees and applicants based on jobrelated qualifications and ability to perform a job. If you require an accommodation during the hiring process or upon hire please inform Human Resources. If a selected applicant requests accommodation during the recruitment process Chubb will consult with the applicant in order to provide suitable accommodation that takes into account the applicants accessibility needs.