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$153k – $187k per year
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In office
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Wij bieden in de Benelux een scala aan verzekeringsproducten voor particulieren, families en bedrijven. Wij hebben onder andere verzekeringsproducten op het gebied van Ongevallen & Welzijn, Financial Lines, Transport, Brand- en Bedrijfsschade, Aansprakelijkheid, Reizen en Overlijdensrisico.

The VP of Artificial Intelligence owns the full AI agenda for our digital business to help accelerate delivery, analytics and CX/MKT skills for 3 growth products (Renters, Pets, Jewelry/Watches). You are a builder who can craft a strategy through defining, shipping, and operating primarily as a senior individual contributor with a multiplier mindset. You will prototype, deploy, and iterate on solutions yourself while coaching the teams around you to adopt and extend what you build.

The right candidate is an entrepreneur who can collaborate and build relationships across a large company (Operations, IT, AI, Digital Studio): someone who has the tenacity to find the shortest path to a working solution, ships it, learns from production, and scales what works. You are equally comfortable presenting a roadmap to senior leaders and debugging a data pipeline on a deadline. You do not wait for perfect conditions. You build with what exists, document what you learn, and raise the bar for everyone who works alongside you.

This role is accountable for working across teams and with external partners to own AI Development Life Cycle (AI-DLC) for 3 growth products to help our digital businesses achieve speed to value. You will own the extension and continuous improvement of that framework across Pets (Healthy Paws), Renters, Jewelry and Watches.

Build and ship, personally:

  • Prototype, deploy, and harden AI/ML and generative AI solutions. Stay close enough to the code, data, and infrastructure to make real architectural calls, unblock others, and ensure production systems are safe and maintainable. This is not a slide-deck leadership role.

Set the roadmap and own the execution:

  • Define the AI strategy across analytics, ML, and generative AI and tie every initiative to a concrete business metric. Distinguish between experiments that teach and investments that scale. Prioritize relentlessly.

Deliver short-term wins without sacrificing long-term outcomes:

  • Ship working solutions in weeks, not quarters, while designing for extensibility across all three product lines. Avoid one-off builds. Every capability you ship should be reusable, governable, and transferable to the teams that will operate it after you move on.

Manage a portfolio of AI capabilities across CX, Digital, and Marketing:

  • Own a library of reusable AI skills these teams can adopt and operate independently. Prioritize which to build, maintain quality and governance across them, and coach teams to use them well so AI adoption scales without becoming a bottleneck.

Customer Experience:

  • Automated ticket triage and routing.
  • AI-drafted support responses and real-time agent copilots.
  • Voice of the Customer (VOC), NPS and sentiment tracking and action plan.
  • Self-service voice and chat assistants.
  • Post-interaction summarization for trends and action planning with Operations.

Digital:

  • On-site search and recommendation engines.
  • Conversational product discovery and personalization.
  • Next-best-action and session-level intent prediction.
  • A/B test analysis, content tagging and metadata enrichment.

Marketing:

  • Generative copy and creative variants.
  • Audience segmentation and lookalike modeling.
  • Campaign performance forecasting and campaign optimization for Marketers.
  • SEO and AEO content strategy, lead scoring and churn prediction for spend optimization.

Think in systems:

  • Diagnose problems at the level of workflows, incentives, and data infrastructure, not just models. Design solutions that hold up when volume scales and team composition changes.

Collaborate across the organization:

  • Partner with Product, Engineering, Data, Operations, Risk, and business unit leaders. Translate ambiguous business problems into scoped technical solutions and bring stakeholders along.

  • Cross-functional partnership is essential for success in this role, not optional.

Own responsible AI:

  • Build and maintain governance, evaluation, and monitoring practices that keep all usage safe, responsible, auditable, and aligned with Chubb standards. Operate within and strengthen the existing AI-DLC framework.

  • Proven track record personally building and shipping production AI/ML and generative AI systems; you can still do the work, not just direct it
  • Demonstrated ownership of the full AI Development Life Cycle, from ideation through requirements, prototyping, deployment, and value measurement. Required.
  • Entrepreneurial operating style: resourceful, bias toward action, comfortable with ambiguity, and able to deliver real outcomes with limited resources
  • Strong systems thinker who designs for extensibility and reuse, not just the immediate problem
  • Ability to coach and multiply impact through people around you without requiring headcount to ship
  • Excellent communicator who earns trust with technical and business partners alike
  • Deep, current knowledge of the AI landscape: models, tooling, infrastructure, and tradeoffs
  • Experience at a leading technology company (Amazon, Microsoft, Meta, or Google) preferred
  • Experience establishing responsible AI and governance frameworks a plus
  • Insurance or regulated industry experience a plus

The pay range for the role is $153,000 to $187,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.

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