AI Technology Leader

Company Details

Company URL: https://www.berkleytechnologyservices.com/

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.

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 with handful of operating units and working with other applications 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., 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

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, infrastructure teams, and applications teams 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

Education & Experience

• 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.

Technology & Domain Expertise

• 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) - we’ll need someone to define and implement

Leadership & Influence

• 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.

Preferred Qualifications

• Experience with intelligent automation, digital workers, or AI-driven process orchestration in insurance operations.
• Familiarity with regulatory frameworks and ethical considerations for AI in financial services (e.g., NYDFS, NAIC, GDPR, AI Act).
• Participation in industry forums, standards bodies, or AI governance initiatives.

What We Offer

• A high-impact leadership role at the forefront of AI transformation in a $14B enterprise.
• Competitive compensation, performance incentives, and executive benefits.
• A collaborative, innovation-driven culture with strong executive sponsorship for AI.
• Opportunities to shape the future of insurance through cutting-edge technology.

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 with handful of operating units and working with other applications 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 Responsibilities1. 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., 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
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, infrastructure teams, and applications teams 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