Principal Enterprise Architect

Workiva•Ames, IA

20h•Remote

About The Position

We are establishing our Enterprise Architecture (EA) function and seeking a Principal Enterprise Architect. This individual is a collaborative, strategic leader to design and implement our core architectural framework. Reporting directly to the CIO of a $1B+ public software organization, you will partner closely with business technology, data, and security leaders to establish architectural standards and build the baseline architecture powering our enterprise AI initiatives. This role begins as an individual contributor with dedicated cross-functional support, carrying a structured roadmap to recruit and lead a dedicated Enterprise Architecture team as the function matures. This is a "builder" role, not a "maintainer" role. You will define what doesn't yet exist and be the connective tissue between business strategy, systems architecture, data architecture, and emerging AI initiatives.

Requirements

10+ years in progressively senior IT/technology roles with degree, 8+ years with an advanced degree, with 5+ years specifically in an enterprise architecture, solutions architecture, or architecture leadership capacity.
Demonstrated experience building or significantly maturing an Enterprise Architecture function, ideally in a mid-size ($500M–$5B revenue) or high-growth environment.
Deep knowledge of business systems architecture (ERP, CRM, financial systems) and data architecture principles.
Direct experience architecting or overseeing AI/ML integration into enterprise systems — including LLM-based tools, AI copilots, or data platforms supporting AI use cases.
Foundational understanding of AI security, data privacy, and governance principles.
Strong understanding of cloud architecture (AWS, Azure, or GCP), integration patterns, and modern data platforms.
Experience working with or managing external consultants/implementation partners.
Excellent communication skills—able to translate complex architecture concepts for both technical teams and executive stakeholders.
Comfortable operating with a high degree of autonomy in a “team of one” environment while building toward a larger function.

Nice To Haves

Prior experience in a publicly traded company, with awareness of SOX, audit, and compliance considerations affecting architecture decisions.
Familiarity with enterprise architecture frameworks (TOGAF, Zachman)—certification is a plus.
Direct experience standing up formal AI governance frameworks or responsible AI policies.
Advanced experience with agentic AI frameworks, MCP (Model Context Protocol), or specific enterprise AI platforms (e.g., Microsoft Copilot Studio, Anthropic Claude, OpenAI enterprise tools).
Background in the software/SaaS industry, understanding both internal enterprise systems and product-side architecture considerations.

Responsibilities

Define and implement the Enterprise Architecture operating model, principles, governance rhythm, and a pragmatic framework tailored to the company’s size and pace.
Develop, maintain, and present core technology standards, reference architectures, and multi-year roadmaps across business systems and data platforms (partnering with consultants as needed for rapid current-state assessment).
Drive formal architecture review processes for major technology investments, ensuring strict alignment with enterprise standards, security, scalability, and cost efficiency.
Define and lead the enterprise AI architecture strategy—including model integration patterns, LLM/agentic frameworks, infrastructure choices (build vs. buy, cloud AI services), and internal AI platform buildouts.
Partner with security, legal, and data governance teams to establish responsible AI policies, data privacy standards, and architectural guardrails for deploying copilots, agents, and automation into core business systems.
Serve as the subject matter expert and advisor to executive leadership on emerging AI architecture trends, risks, and strategic implications.
Define data architecture standards (data governance, flow patterns, master data management) and API integration frameworks in close partnership with data and engineering teams.
Evaluate and rationalize the application portfolio across business systems to actively identify consolidation opportunities, reduce technical debt, and eliminate system duplication.
Act as a trusted architectural authority across business, engineering, and security functions, building consensus around complex technology decisions without direct authority.
Build the business case for expanding the EA capability, taking ownership of hiring, mentoring, and managing future architects as the function matures.