AI-Ready Knowledge Architect

AI-Ready Knowledge Architect

KeyBank is seeking an AI-Ready Knowledge Architect to design and maintain the enterprise information architecture. This role is crucial for cataloging KeyBank’s data, enabling self-service understanding, and supporting AI-ready data and knowledge usage. You will define and enforce standards for data modeling, taxonomy, semantic structures, and knowledge representation to ensure consistency and clarity across the organization.

Key Responsibilities

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies for shared understanding and discoverability.
• Design and evolve information and semantic models to make enterprise data AI-ready for various use cases, including traditional analytics, BI, applied machine learning, and LLM-based experiences.
• 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.
• Provide authoritative guidance on semantic conflicts, resolving definition discrepancies and mediating cross-domain dependencies.
• Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts.
• Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI-enabled workflows.
• Identify simplification opportunities to reduce redundancy and promote canonical sources for improved trust and efficiency.
• Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context support trustworthy AI outcomes.
• Serve as a thought partner, providing insights to shape governance strategy and roadmaps based on modeling, catalog adoption, and AI enablement.

Required Experience

• 10+ years of experience with data, metadata, and reference data frameworks, including metadata management and/or data quality monitoring.
• Experience leading the development of enterprise business glossaries, domain models, and ontologies for semantic consistency 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 abilities.
• Hands-on experience implementing and scaling an Enterprise Data Catalog or metadata repository (Alation or equivalent).
• Understanding of how semantic models, metadata, and knowledge representation enable applied AI and LLM use cases.
• Strong business acumen in relating data to business process drivers and performance management.
• Collaborative, team-focused delivery experience driving 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 Used

• Knowledge Graphs (Neo4j, Stardog, Amazon Neptune / Azure Cosmos DB)
• 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 (Vector databases like Pinecone, Weaviate, Azure AI Search; hybrid RAG)

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 Skills/competency

• AI-Ready Knowledge Architect
• Data Modeling
• Ontologies
• Taxonomy
• Semantic Structures
• Metadata Management
• Data Governance
• Enterprise Data Catalog
• Applied AI
• LLM