Principal Enterprise Architect

Clarivate•Kansas City, KS

14h•Hybrid

About The Position

Clarivate is seeking a Principal Enterprise Architect, AI Strategy & Enablement, to join its Enterprise Application and Data Services organization in the US. This senior individual-contributor role will shape enterprise AI adoption by translating business goals into a practical, governed architecture strategy and roadmap. The architect will serve as a senior architectural authority for AI across enterprise applications and data platforms, helping ensure investments are built on strong data foundations and delivered responsibly, securely, and at scale. The role focuses particularly on generative AI and the Microsoft AI ecosystem, including Copilot and Azure OpenAI. The position partners with technology and business leaders across functions such as HR, Finance, Legal, and Sales. It offers significant opportunity to influence enterprise AI direction, mentor architects, and turn high-value AI opportunities into scalable solutions. The Enterprise Data & Integration Services team includes enterprise and solution architects, Product Owners, software engineers, data analysts, and other technology professionals who support enterprise applications, data, integration, and emerging AI capabilities. The role partners closely with IT leadership, Enterprise Application Leadership teams, Product Owners, and business functions to help AI investments drive efficiency, scalability, colleague experience, and compliance. The role is full-time and permanent, and is hybrid at offices in Philadelphia, Pennsylvania; Kansas City, Missouri; or Ann Arbor, Michigan.

Requirements

Bachelor’s degree or equivalent relevant professional experience.
At least 10 years of relevant professional experience, including at least 5 years in enterprise, solution, or data architecture roles.
At least 2 years of experience architecting and delivering AI/ML or generative AI solutions in a scaled environment.
At least 5 years of experience in data architecture and data governance, including data platforms, data quality, and data foundations for AI at scale.
At least 5 years of experience partnering with and influencing senior stakeholders, including leading technology or architecture initiatives without direct authority.
At least 3 years of experience driving technology change management, AI literacy, training, enablement, or adoption programs for business and/or technology teams.
At least 3 years of experience mentoring or developing architects or other technology professionals.

Nice To Haves

Experience with the Microsoft AI ecosystem, such as Microsoft Copilot and Azure OpenAI.
Experience architecting generative AI, copilot, or agent-based capabilities within enterprise applications.
Experience evaluating AI technologies, vendors, and platforms and contributing to build-versus-buy decisions.
Experience establishing or operating structured AI use-case intake and prioritization processes.
Experience partnering with business functions such as HR, Finance, Legal, or Sales on enterprise AI initiatives.
Experience defining or measuring AI adoption, value realization, or architectural compliance.

Responsibilities

Shape the enterprise AI strategy, target-state architecture, and multi-year roadmap across enterprise applications and data.
Establish scalable architecture patterns and standards for generative AI, copilots, and agent-based capabilities; evaluate emerging technologies and build-versus-buy opportunities.
Define AI governance and responsible AI guardrails in partnership with Security, Legal, Risk, and Compliance to address privacy, security, regulatory, and audit requirements.
Conduct architecture reviews and ensure data quality, lineage, access, and classification support trusted and secure AI solutions.
Establish a structured approach to identify and prioritize high-value AI use cases across functions including HR, Finance, Legal, and Sales.
Partner with Product Owners and technology leaders to assess use-case value, feasibility, and risk, and guide successful pilots into scalable production solutions.
Drive AI literacy and adoption through training, communication, stakeholder engagement, and partnership with business and change leaders.
Define measures of AI adoption, value realization, and architectural compliance.
Mentor architects and provide guidance across AI initiatives.
Influence technology decisions and provide architectural leadership across teams.