AI Product Manager, Blockchain Insurance

**MFI (Bermuda) Limited** is an entity linked to mF International Limited (Nasdaq: MFI), which applied for a Bermuda Class IILT Insurance License through the Bermuda Monetary Authority's Insurance Regulatory Sandbox to launch a digital asset-denominated insurance business. As part of our ongoing expansion, we are looking to appoint a **Product Manager** who combines a strong understanding of insurance with hands-on experience delivering AI products. This position will drive the adoption of large language models, AI agents, and related technologies across our insurance business. Internally, you will use AI to improve core processes such as underwriting, claims, customer service, compliance, and operations. Externally, you will develop AI-native products for customers and brokers. You will also be accountable for the performance and risks of these AI applications within the applicable regulatory framework. **Key Responsibilities** **AI Use-Case Planning and Industry Research** - Map our end-to-end business processes, from application to claims, to identify where AI can add value. Assess business impact, feasibility, and compliance risk, and develop a phased AI roadmap. - Monitor developments in the use of AI across the insurance industry, including AI-native insurers, InsurTech providers, and advances in large language models. Produce competitive analysis and technology selection recommendations. **Internal AI-Enabled Process Transformation** - Lead the implementation of AI in internal business processes, including intelligent underwriting, claims document extraction and review, knowledge base Q&A for customer service, KYC/AML and compliance automation, and operational reporting. - Work with actuarial, compliance, and operations teams to translate business rules and operating procedures into standardized workflows that AI systems can execute. Design appropriate human-review and exception-handling controls to ensure outputs remain controlled and auditable. **External AI-Native Products** - Lead the planning and delivery of AI products for customers and brokers, including AI insurance advisers, intelligent application assistants, policy servicing agents, and tools that explain benefit illustrations. - Design integrations between AI products and existing new business and policy administration systems. Embed disclosure and compliance requirements into product interactions and generated content. **AI Platform Development and Quality Governance** - Build reusable AI infrastructure, including model selection and integration, retrieval-augmented generation (RAG) knowledge bases, and prompt management, so that business teams can adopt AI capabilities efficiently. - Establish model quality controls and evaluation processes to improve output accuracy, manage hallucination risk, and prevent mis-selling. - Oversee data compliance for AI applications, ensuring that personal data and cross-border data transfers meet applicable BMA regulatory requirements. - Define business performance metrics for AI initiatives, such as automation rates, processing times, conversion rates, error rates, and human-intervention rates. Use these metrics to evaluate return on investment and guide continuous improvement. **Qualifications & Experience** - Bachelor's degree or above; a background in computer science, artificial intelligence, data science, finance, insurance, or a related field is preferred. - At least five years of product management experience, including two or more years working on AI or large language model products, with a proven track record of taking an AI initiative from concept to production. - Experience designing products built on LLMs and AI agents, with practical knowledge of prompt engineering, RAG, tool calling, evaluation dataset development, and performance evaluation. - A solid understanding of the insurance lifecycle, including application, underwriting, policy issuance, policy servicing, surrender, and claims, with the ability to discuss detailed business requirements directly with actuarial and compliance teams. - Ability to translate complex business rules into AI-executable workflows, user interactions, and exception-handling logic, and to work with engineering teams to ensure accurate implementation. - A data-driven approach to product management, with the ability to use data to identify problems and validate the effectiveness of AI initiatives. - Understanding of model risk governance, including hallucination controls, explain ability assessments, human-review mechanisms, post-launch regression testing, and monitoring. - A strong sense of ownership and attention to detail, with the ability to oversee AI initiatives from pilot through scaled deployment. - Familiarity with digital assets, stablecoins such as USDC, or Bitcoin-denominated insurance products.