AI Technology Leader

Responsibilities

• Define and evolve the enterprise-wide technology strategy for Generative and Agentic AI, aligned with business goals and operational priorities.
• Partner with the Corporate AI Leader to translate business needs into scalable AI capabilities and reusable platform components.
• Serve as a strategic advisor to senior leadership on AI platform direction, architectural decisions, and emerging technologies.
• Lead the design of a modular, secure, and scalable AI architecture that supports generative and agentic AI use cases across underwriting, claims, policy servicing, actuarial, finance, HR, IT and customer engagement.
• Define reference architectures, reusable components, and integration patterns for AI agents, orchestration frameworks, and LLM-based services.
• Ensure alignment with enterprise architecture, cloud strategy, and data platform capabilities.
• Lead a small, high-impact team of AI engineers and product managers responsible for building and enabling AI capabilities across the enterprise.
• Establish foundational practices, delivery models, and team culture as the function matures.
• Provide strategic direction, coaching, and prioritization to ensure delivery of high-value solutions.
• Evaluate and recommend enterprise-grade AI platforms, orchestration frameworks (e.g., LangChain, Semantic Kernel), vector databases, and agentic AI toolkits.
• Guide the development of a shared AI services layer (e.g., prompt libraries, RAG pipelines, agent orchestration) to accelerate delivery and reuse.
• Stay current with the evolving AI technology landscape and assess applicability to the insurance domain.
• Ability to review technical and business proposals and guide teams to land on optimal AI solutions.
• Collaborate with the AI Governance team to ensure that AI solutions are designed and deployed in compliance with regulatory, ethical, and risk management standards.
• Contribute to the development of policies and frameworks for responsible AI, including transparency, explainability, and human oversight.
• Ensure that technology decisions support auditability, traceability, and model lifecycle management.
• Discern between Gen AI related risks, operational automation/business risks and evangelize the right adoption framework.
• Partner with enterprise architects, infrastructure teams, and applications teams to ensure seamless integration of AI into existing systems and workflows.
• Partner with Corporate AI Leader to ensure business priorities are reflected in the implementation plans.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field; MBA or equivalent business education is a plus.
• 12+ years of experience in enterprise technology leadership roles, with at least 3 years focused on AI/automation strategy, architecture, or platform enablement.
• Experience in commercial or specialty insurance, financial services, or other regulated industries is strongly preferred.
• Strong understanding of Generative AI (LLMs, RAG, prompt engineering) and Agentic AI (multi-agent systems, autonomous workflows) from a platform and architecture perspective.
• Familiarity with enterprise AI platforms (e.g., Azure OpenAI, AWS Bedrock, Google Vertex AI), orchestration frameworks, and cloud-native design.
• Knowledge of core insurance systems and processes (e.g., Guidewire, Duck Creek, policy admin, claims, underwriting) is a plus although not required.
• Strong understanding of modern application development frameworks and agile.
• Proficiency in MLOps practices and tools (CI/CD for ML, containerization, orchestrated model deployment), developing reproducible deployment pipelines).
• Proven experience leading cross-functional technology teams, including product managers and engineers.
• Strong ability to influence senior stakeholders and drive enterprise-wide alignment.
• Excellent communication and storytelling skills to articulate complex AI concepts to both technical and non-technical audiences.