Chief AI Architect

The Chief AI Architect (CAIA) serves as the enterprise design authority for artificial intelligence at STERIS and leads the AI Center of Excellence (AI CoE) delivery organization, owning AI and agentic-AI architecture standards, solution reusability, technical-debt governance, and model/platform strategy end-to-end from proof-of-concept through production. Reporting to the Vice President & Chief Information Officer, the CAIA converts validated AI proof-of-concept value into governed, production-grade AI capability that supports the company growth strategy while managing regulatory and quality risk. As a peer to the Chief Enterprise Architect, the CAIA owns AI solution architecture, model strategy, and agentic-AI build decisions, while the Chief Enterprise Architect retains enterprise AI governance, policy, and audit-readiness oversight through the Architecture Review Board. The CAIA leads the AI CoE’s delivery pods (Product Management, POC, Development, and Operations) and drives a prioritized, value-scored AI project pipeline.

• AI CoE delivery leadership (20%). Lead the AI Center of Excellence delivery organization (Delivery Lead, AI Product Management, POC “Factory,” Development, and AI Command Center/Operations pods); sustain a governed, prioritized pipeline of active AI projects from proof-of-concept through production.
• AI production operations (10%). Own monitoring, drift detection, and incident response for live AI workloads (est. 8–12 today); ensure production AI meets enterprise reliability, security, and quality standards.
• Responsible-AI execution & governance partnership (10%). Partner with the Chief Enterprise Architect and AI Governance Steering Committee/Review Board to execute human-in-the-loop, fail-closed controls at the solution level; build to EU AI Act, FDA CSV/CSA (GAMP 5, 21 CFR Part 11) requirements as directed by governance.
• Demand pipeline & business translation (10%). Direct AI Product Managers in translating business challenges into a prioritized, value-scored backlog; serve as the technical counterpart to business stakeholders on use-case feasibility and value.
• Data & AI platform partnership (8%). Partner with the Director, Data Engineering & Platform and Director, Data Governance & Management to ensure AI solutions run on trusted, governed data foundations.
• Talent, training & AI adoption (7%). Support the AI Enablement & Adoption Lead and AI Academy/Community programs; mentor AI Development and POC talent; build the CoE succession plan.
• Consultant-to-FTE transition & vendor management (10%). Own the transition of AI delivery from SOW-based consulting to a permanent, budgeted FTE organization; partner with Procurement and HR on hiring, onboarding, and AI tooling vendor consolidation.
• Leadership: Provides strategic leadership and direction for the function, leading and developing high-performing teams, driving organizational priorities, fostering a culture of accountability and collaboration, and ensuring the successful execution of business objectives aligned with the company's long-term goals.

• 15 overall years of experience including: 8+ years in technology, 4+ years in AI/ML, data science, or enterprise architecture roles, and 2+ years leading an AI delivery function or team.
• Demonstrated production delivery of AI/GenAI solutions at enterprise scale; proven ability to convert proof-of-concept work into governed, production-grade capability.
• Experience standing up or scaling an AI Center of Excellence or comparable delivery organization.
• Regulated-industry experience (medical device, life sciences, healthcare, or similar) preferred; familiarity with FDA CSV/CSA (GAMP 5, 21 CFR Part 11), EU AI Act, and data-privacy (GDPR) obligations a plus.
• Progressive technology leadership experience
• Proven ability to lead multidisciplinary teams of AI professionals preferably for roles that support development and an AI Command Center/Operations.
• AI/GenAI and agentic-AI architecture, model strategy, and platform evaluation (e.g., Azure AI Foundry, Claude, Copilot).
• MLOps, production AI monitoring, drift detection, and incident response.
• Delivery organization leadership: pipeline management, resourcing, and pod-based delivery models (POC, development, operations).
• Executive stakeholder management and business translation (value-scoring, backlog prioritization).
• Team building, mentoring, and succession planning for a technical delivery organization
• Demonstrated success defining and executing enterprise-wide AI strategies aligned with business objectives and digital transformation goals.
• Experience influencing C-suite executives and senior business leaders on AI investments, innovation roadmaps, and technology strategy.
• Strong track record of building high-performing teams through coaching, mentoring, succession planning, and talent development.
• Proven leadership in driving organizational change and fostering AI adoption across business functions.
• Demonstrated ability to manage large-scale AI programs, budgets, vendor relationships, and strategic technology partnerships.
• Experience leading enterprise architecture decisions and integrating AI solutions into complex technology ecosystems.
• Strong stakeholder management skills with the ability to align business, technology, legal, security, and compliance teams around strategic AI initiatives.