Technology Head of AI

Location: Greater London

## Technology Head of AIApplylocations:
London time type:
Full time posted on:
Posted 4 Days Agojob requisition :
JR140
** The role
** Willis Re is a technology led reinsurance broker built on a cloud native, modular and data driven platform. As the technology Head of AI & Emerging Tech, you will own the overall technology strategy and the roadmap for AI, automation and next generation capabilities. As a member of the technology leadership team, you will turn innovation into scaled capabilities across broking, placement, analytics, and client servicing—balancing speed with safety, and experimentation with operational excellence.

You will partner closely with the Product Manager, Brokers and business leaders to design simple and scalable solutions and move them from pilot to production with clear accountability. Operating in a hybrid delivery model, you will set standards, govern risk and ensure alignment to global architectures and security requirements, while enabling regional flexibility where needed.

Key responsibilities
* Define and own the technology strategy for AI, aligned to business priorities; translate value propositions into a roadmap.
* Lead delivery of AI solutions across pricing support, submission triage, document and market data extraction, client insight, workflow automation and co pilot experiences for employees.
* Establish responsible AI governance and controls in partnership with Cyber, Data Protection and Legal, covering model risk, data privacy, transparency, human in the loop and auditing.
* Build the target operating model for AI engineering and MLOps, including model lifecycle management, monitoring, incident response, versioning and cost/performance optimisation.
* Set global standards for AI platforms, tool chains and integration patterns; ensure interoperability with enterprise data platforms and adherence to security and compliance requirements.
* Drive rapid experimentation with clear exit criteria; scale successful pilots into reliable, maintainable services using automated testing, observability and release practices.
* Develop and manage strategic vendor and partner relationships, balancing build vs. buy decisions and negotiating commercial and risk terms that protect value.
* Provide executive level communication and storytelling on technology strategy, risks and outcomes; partner effectively with Product Managers, Brokers and clients to shape solutions that fit market workflows.
* Assist Product Managers to ensure solutions land successfully with business teams.
* Maintain horizon scanning and technology assessment, identifying pragmatic opportunities to introduce new capabilities that enhance agility and global scalability.
** About you
** You are a business minded technology leader who turns AI and advanced technology into practical capabilities. You combine strategic clarity with hands on depth, moving comfortably from business conversation to solution design and delivery oversight, and you anchor decisions in risk and value.  You thrive in a start up environment and are comfortable operating beyond your usual remit to get things done—partnering with business, engineers and regional leaders to unblock delivery and drive adoption.

You communicate crisply with business leaders, make trade offs explicit and hold clear ownership for outcomes.
** Skills and experience
*** Significant experience leading digital transformation, with proven delivery of AI, automation and emerging technology in complex, cloud first environments.
* Proven capability to architect end to end solutions as well as deliver them, from reference architectures and integration patterns through to production rollout and adoption.
* Proven delivery of AI/ML and GenAI solutions in production, including document intelligence, NLP, search/summary, recommendation, decision support and workflow automation.
* Strong grasp of responsible AI, security and compliance, including model risk management, privacy, data residency, human oversight and auditability.
* Hands on understanding of AI/MLOps practices and platforms, including model lifecycle, observability, cost control, CI/CD, feature stores and data integration.
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