AI-Ready Context Engineer, Ontologist

KeyBank

AI-Ready Context Engineer/Ontologist shaping KeyBank’s banking data architecture, taxonomies, and ontologies. Enabling governed analytics, knowledge graphs, and trustworthy AI/LLM experiences.

Posted 8/14/2026full-timeBrooklyn • Ohio • 🇺🇸 United StatesSeniorLead💰 $96,000 - $181,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in data governance, metadata management, and the development of enterprise data models and taxonomies. Proven ability to operationalize data frameworks and collaborate with cross-functional teams to drive AI-enabled outcomes.

Highest-signal resume keywords

10+ Years Experience In Data ManagementMetadata Management And Data Quality MonitoringEnterprise Data Catalog Implementation (Alation)Data Governance And Master Data ManagementSemantic Models And Knowledge Representation

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ModelingMetadata ManagementData Quality MonitoringBusiness Glossary DevelopmentData LineageProcess EngineeringSemantic StructuresAnalytics SupportAI EnablementBusiness Analysis

Soft Skills

Strong Verbal And Written CommunicationCollaborative Team-Focused DeliveryStrategic Thinking

Tools & Technologies

AlationNeo4jStardogAmazon NeptuneAzure Cosmos DB (Graph)OWLRDFSKOSProtégéMicrosoft Purview

Industry Keywords

Data GovernanceMetadata ManagementEnterprise Data ModelsTaxonomyOntologiesAI-Enabled WorkflowsBusiness Process DriversPerformance ManagementCanonical SourcesCross-Domain Dependencies

Tech Stack

Tools & technologies

AzureNeo4j

About the role

Key responsibilities & impact

Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies
Design and evolve information and semantic models supporting analytics, BI, 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
Resolve semantic conflicts, harmonize terms, and mediate cross-domain dependencies
Define domain boundaries, shared dimensions, and semantic contracts for the enterprise data product framework
Confirm and document prioritized metadata elements for business processes, analytical use cases, and AI-enabled workflows
Identify simplification opportunities, reduce redundancy, converge overlapping datasets, and promote canonical sources
Partner with analytics, data science, and AI engineering teams to support explainable, governed, and trustworthy AI outcomes
Provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps

Requirements

What you’ll need

10+ years of experience working with data, metadata, and reference data frameworks
Experience in metadata management and/or data quality monitoring
Experience leading enterprise business glossaries, domain models, and ontologies
Knowledge of data governance, data quality, master data management, data lineage, and metadata management
Experience establishing and operationalizing metadata governance functions, including policies, standards, roles, and controls
Strong verbal and written communication skills
Hands-on experience implementing and scaling an Enterprise Data Catalog or metadata repository, such as Alation or equivalent
Understanding of semantic models, metadata, and knowledge representation for applied AI and LLM use cases
Strong business acumen relating data to business process drivers and performance management
Collaborative, team-focused delivery experience across enterprise data, analytics, and technology organizations
Strategic thinking and ability to translate enterprise objectives into actionable plans and measurable outcomes
Excellent knowledge of data and metadata management principles, business analysis, and process engineering
Knowledge of knowledge graphs and technologies including Neo4j, Stardog, Amazon Neptune, Azure Cosmos DB (Graph), OWL, RDF, SKOS, Protégé, TopBraid, Alation, Collibra, Microsoft Purview, DataHub, Pinecone, Weaviate, and Azure AI Search

Benefits

Comp & perks

Base salary range of $96,000.00 - $181,000.00 annually
Eligibility for incentive compensation, which may include production, commission, and/or discretionary incentives
Flexible options in circumstances where roles can be performed effectively in a mobile environment
Flexible, inclusive work environment
Challenging projects
Accessible leaders
Opportunities to grow in your position and your career
Supportive teammates