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 Objective:

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 cross-functional 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 proof-of-concepts, 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 Chubb's 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.
Cross-Functional Collaboration: Partner with business stakeholders, risk management, legal, and compliance teams to ensure a holistic approach to AI governance. Facilitate cross-departmental 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:

Bachelor's degree in computer science, or a related STEM field is required.
Master's 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 problem-solving 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, Scikit-learn) 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.

Governance Skills:

Regulatory Compliance and Risk Management: Deep understanding of compliance requirements, data governance, and legal considerations surrounding AI usage.
Cost-Benefit 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 job-related 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 applicant's accessibility needs.

VP, Head of Global AI Architecture & Governance jobs

VP, Head of Global AI Architecture & Governance

Never Miss a New Opportunity