AI Automation Architect

Company Details

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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 looking for outstanding individuals who will bring unique perspectives, insight and innovation to our teams. BTS, a member company of W. R. Berkley Corporation, has facilities located in Des Moines, Iowa and Wilmington, Delaware. Our functions include working with various third parties to develop, integrate, and support insurance systems of WRBC's operating units. BTS strives to provide these functions in a holistic manner including helpdesk support, system connectivity, and operational support. Additional responsibilities include coordinating communications regarding best practices in the use of our supported systems and researching new technology. At BTS, there are opportunities associated with being a part of an established and empowering corporation while maintaining a positive personal working environment. Additionally, we provide a competitive compensation and benefits package including a casual dress code. BTS is constantly growing and expanding to meet the changing demands of one of the most successful insurance organizations in the world. Visit us at berkley-bts.com to learn more information.

The Company is an equal employment opportunity employer. 

Responsibilities

The AI Automation Architect designs, builds, and maintains the automation and AI-enabled capabilities that make Berkley’s Governance, Risk & Compliance (GRC) function faster, more consistent, and more audit-ready. The role turns manual, repetitive compliance work — evidence collection, control testing support, exception handling, and reporting — into governed, automated workflows, freeing IT Compliance and operating-unit personnel to focus on judgment, risk decisions, and control ownership. 

Working within IT GRC and in close partnership with Information Security, Internal Audit, and the operating units, the engineer builds automations on the enterprise GRC platform (ServiceNow GRC/IRM and Archer), integrates control and evidence data across systems, and applies AI responsibly to accelerate compliance activities. Consistent with BTS’s “security-first” and “use AI to work smarter” principles, this position acts as a force multiplier for the compliance team rather than a replacement for it — accountability, oversight, and risk acceptance remain with people. 

• Automation & AI Engineering: Design, develop, and maintain GRC automations and AI-enabled solutions that streamline compliance processes, ensuring each solution complies with security, privacy, and governance requirements. 
• Control Evidence & Testing Support: Automate the collection, validation, and packaging of control evidence for SOX, NYDFS Part 500, and internal control assessments — reducing manual gathering and improving completeness and consistency. 
• Exception & Workflow Automation: Build and improve exception intake, routing, reporting, and dashboards within ServiceNow GRC/IRM and Archer; support the migration of GRC processes onto the strategic platform. 
• Integration & Data: Integrate control, risk, and evidence data across GRC, ITSM, identity, and security tooling via APIs and connectors to create reliable, reusable data pipelines and reporting. 
• Applied AI: Apply AI responsibly to draft first-pass control narratives, summarize findings, map controls to frameworks (NIST CSF 2.0, NYDFS Part 500), and accelerate analysis — with human review retained for all decisions. 
• Documentation: Create and maintain clear process and technical documentation for every automation, including run books, data lineage, and control mappings, so solutions remain auditable and supportable over time. 
• Security First: Implement a security-first practice, embedding least-privilege access, logging, and change-control into every automation; ensure AI and automation use aligns with the company AI Policy and GRC governance. 
• Business Partnership: Partner with IT Compliance analysts, Internal Audit, InfoSec, and OU compliance personnel to identify high-value automation opportunities, gather requirements, and drive adoption of delivered capabilities. 

Qualifications

• Hands-on automation building. Demonstrated experience turning manual, fragmented processes into engineered, automated workflows — with concrete examples of automations built and shipped, not just advised on. 

• Programming and scripting. Proficiency in Python and comfort building and consuming APIs / REST integrations to move and connect data across systems. 

• Workflow and integration tooling. Practical experience with workflow-automation and orchestration tools, plus building reusable pipelines and integrations that others can consume. 

• Applied AI judgment. Working experience with applied AI — agents, retrieval-augmented generation (RAG), and LLM-assisted workflows — and sound judgment on when AI adds value versus when deterministic automation is the better choice. 

• Data engineering fluency. Ability to structure, transform, and move data reliably across systems as the foundation for automation. 

• Security-first mindset. Designs with security, oversight, and accountability in mind; keeps human judgment and review in the loop where it matters. 

• Communication. Can explain technical work clearly to non-technical stakeholders and leadership. 

• Autonomy and influence. Comfortable operating with significant autonomy and influencing adoption across teams without direct authority. 

Preferred Qualifications (Nice-to-Haves) 

• Security domain exposure. Familiarity with one or more security domains — identity, cloud security, GRC, security operations, or AI security. 

• Cloud and sandbox experience. Experience working in Azure and building or operating in lab / sandbox environments. 

• Reusable patterns and standards. Track record of creating reusable automation patterns, reference designs, or standards that scale across multiple teams or business units. 

• Coaching orientation. A force-multiplier, coaching-oriented style that raises the whole team’s leverage rather than centralizing all delivery on one person. 

• Enterprise scale. Experience delivering solutions adopted broadly across a large or distributed organization. 

Education and Experience 

• Education. Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field — or equivalent practical experience. 

• Experience. Several years of hands-on experience in software/automation engineering, data/integration engineering, or applied AI, including delivery of production-grade automation. 

Core Competencies 

Aligned to the WRB Competency Model and our Behavioral Interviewing focus areas (Innovation and Extreme Ownership): 

• Innovation. Applies modern AI and automation pragmatically to solve real problems. 

• Extreme ownership. Takes end-to-end accountability for what is built and how it performs. 

• Collaboration. Works across boundaries in a non-territorial, shared-talent model. 

• Judgment. Balances speed with responsible, secure, well-governed delivery. 

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