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AI Technology Leader

Job in Urbandale, Polk County, Iowa, 50322, USA
Listing for: W. R. Berkley Corporation
Full Time position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Company Details

Company URL: https://

Berkley Technology Services (BTS) is a dynamic company committed to providing world class IT services. We offer a unique culture, enabling our team members to be on the cutting edge of technology while delivering high quality solutions.

We are a $14B commercial and specialty insurance provider delivering innovative, data‑driven risk solutions to clients across a wide range of industries. As part of our enterprise transformation, we are investing in next‑generation AI technologies to reimagine how we operate, serve customers, and manage risk.

The Company is an equal opportunity employer.

Responsibilities

We are seeking a strategic, enterprise‑focused AI Technology Leader to lead the architecture, platform strategy, technology standardization and enablement of Generative and Agentic AI capabilities across the organization. This is a leadership role focused on incubating ideas for automation, implementation of those ideas within a handful of operating units and working with other application development and data teams to scale. This role will solely focus on process automation and not predictive model development or data science.

This leader will lead a small, early‑stage team of AI engineers and product managers, work in close partnership with the Corporate AI Leader and Chief Data & Analytics Officer, and collaborate across technology, data, and governance functions to deliver scalable, secure, and responsible AI capabilities. The function is in its infancy, offering a unique opportunity to shape foundational capabilities and influence enterprise‑wide transformation.

Key Responsibilities 1. Enterprise AI Technology Strategy
  • 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.
2. Platform Architecture & Enablement
  • 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.
3. Team Leadership
  • Lead a small, high‑impact team of AI engineers and product managers responsible for building and enabling AI capabilities across the enterprise. Some of these members will work in matrix reporting relationships.
  • 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.
4. AI Ecosystem & Technology Selection
  • Evaluate and recommend enterprise‑grade AI platforms, orchestration frameworks (e.g., Lang Chain, 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.
5. Governance & Risk Collaboration
  • 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.
6. Cross‑Functional Alignment
  • Partner with enterprise architects,…
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