AI-Ready Knowledge Architect

Posted Yesterday
Be an Early Applicant
2 Locations
In-Office or Remote
96K-181K Annually
Expert/Leader
Fintech
The Role
Design and maintain enterprise information architecture, including domain models, taxonomies, ontologies, and metadata to make data AI-ready. Operationalize models via enterprise data catalog (Alation), resolve semantic conflicts, define metadata standards, and partner with analytics and AI teams to enable governed, explainable AI and downstream BI/LLM use cases.
Summary Generated by Built In

Location:

4910 Tiedeman Road, Brooklyn Ohio

JOB DESCRIPTION:

The AI-Ready Knowledge Architect plays a critical role in designing and maintaining the enterprise information architecture essential for cataloging KeyBank’s data for self‑service understanding and enabling AI‑ready data and knowledge usage. This role defines and enforces standards for data modeling, taxonomy, semantic structures, and knowledge representation to ensure consistency, interoperability, and clarity across the organization.

The AI-Ready Knowledge Architect partners closely with business and technology teams to develop and maintain the enterprise data domain model and ontologies that support governance frameworks, trusted analytics, and downstream consumption across business intelligence (BI), applied AI/ML, and Large Language Model (LLM) use cases. Success in this role requires the ability to translate complex theoretical concepts into scalable, governed information structures that drive adoption of the data catalog, support emerging AI capabilities, and deliver measurable value to colleagues.

ESSENTIAL JOB FUNCTIONS:

  • Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets.
  • Design and evolve information and semantic models that make enterprise data AI‑ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM‑based experiences (e.g., search, retrieval‑augmented generation, and copilots).
  • Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation).
  • Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns.
  • Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross‑domain dependencies to establish trusted, reusable business meaning.
  • Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts that enable cross‑domain interoperability and AI consumption.
  • Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI‑enabled workflows, ensuring alignment with governance standards and risk expectations.
  • Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms.
  • Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes.
  • Serve as a thought partner, provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps.

REQUIRED EXPERIENCE:

  • 10+ years of experience working with data, metadata, and reference data frameworks, including experience in metadata management and/or data quality monitoring
  • Experience leading the development of enterprise business glossaries, domain models, and ontologies to enable semantic consistency, shared understanding, and AI ready data usage.
  • Demonstrated experience with data management concepts including data governance, data quality, master data management, data lineage, and metadata management.
  • Proven ability to establish and operationalize metadata governance functions, including policies, standards, roles, and controls.
  • Demonstrated verbal and written communication skills, with strong data, metadata, and governance storytelling that drives adoption and influences stakeholders.
  • Hands on experience implementing and scaling an Enterprise Data Catalog or metadata repository (Alation or equivalent), including curation workflows and adoption strategies.
  • Understanding of how semantic models, metadata, and knowledge representation enable applied AI and LLM use cases, such as search, question answering, and decision support.
  • Strong business acumen in relating data to business process drivers and performance management, with a value delivery mindset.
  • Collaborative, team focused delivery experience that drives outcomes across enterprise data, analytics, and technology organizations.
  • Strategic thinker with the ability to translate enterprise objectives into actionable plans and measurable outcomes.
  • Excellent knowledge of data and metadata management principles, business analysis, and process engineering.

TECHNOLOGIES:

Knowledge Graphs

Neo4j

Stardog

Amazon Neptune / Azure Cosmos DB (Graph)

Ontology & Semantic Modeling

OWL / RDF / SKOS

Protégé

TopBraid

Stardog Studio

Enterprise Data & Knowledge Catalogs

Alation

Collibra

Microsoft Purview

DataHub

Knowledge Modeling Techniques

Ontologies & domain models

Business vocabularies & taxonomies

Semantic normalization

Entity & relationship modeling

AI Context Delivery (Grounding Layer)

Vector databases (Pinecone, Weaviate, Azure AI Search)

Graph + vector retrieval (hybrid RAG)

Metadata‑driven prompt context

COMPENSATION AND BENEFITS

This position is eligible to earn a base salary in the range of $96,000.00 - $181,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.

Please click here for a list of benefits for which this position is eligible.

Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.

Job Posting Expiration Date: 07/31/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.

Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing [email protected].



#LI-Remote

Skills Required

  • 10+ years experience working with data, metadata, and reference data frameworks, including metadata management and/or data quality monitoring
  • Experience leading development of enterprise business glossaries, domain models, and ontologies
  • Demonstrated experience with data governance, data quality, master data management, data lineage, and metadata management
  • Proven ability to establish and operationalize metadata governance functions, including policies, standards, roles, and controls
  • Strong verbal and written communication skills with data/metadata storytelling to drive adoption and influence stakeholders
  • Hands-on experience implementing and scaling an Enterprise Data Catalog or metadata repository (Alation or equivalent), including curation workflows and adoption strategies
  • Understanding of how semantic models, metadata, and knowledge representation enable applied AI and LLM use cases (search, QA, decision support)
  • Strong business acumen relating data to business processes and performance management with a value delivery mindset
  • Collaborative, team-focused delivery experience across enterprise data, analytics, and technology organizations
  • Strategic thinker able to translate enterprise objectives into actionable plans and measurable outcomes
  • Excellent knowledge of data and metadata management principles, business analysis, and process engineering

KeyBank Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about KeyBank and has not been reviewed or approved by KeyBank.

  • Retirement Support A dollar-for-dollar 401(k) match up to 7% of eligible pay is positioned as a standout element of the total rewards package. Additional financial programs like discounted stock purchase and banking discounts further strengthen perceived long-term value.
  • Leave & Time Off Breadth A pooled PTO bank with amounts that scale by level and tenure is described as a meaningful benefit and a retention lever. Paid parental leave is also included, adding to the breadth of time-off support.
  • Wellbeing & Lifestyle Benefits Wellness incentives tied to HSA contributions and company-sponsored health and wellbeing programs add tangible non-cash value. A Lifestyle Spending Account and counseling resources expand support beyond traditional medical coverage.

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The Company
Cleveland, OH
16,053 Employees
Year Founded: 1949

What We Do

At KeyBank we’ve made a promise to our clients that they will always have a champion in us. To deliver on our promise, we’re committed to building a team of engaged employees who do the right thing for our clients and shareholders, and help them achieve financial wellness each and every day.

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