AI-Ready Context Engineer/ Ontologist

KeyBank; United States; Hybrid; USD 96,000 - 181,000; Full time

Job summary

KeyBank seeks an AI-Ready Context Engineer/Ontologist to design enterprise data models, taxonomies and ontologies supporting governance, trusted analytics and AI-ready data usage.

The role partners with business and technology teams to maintain the enterprise data domain model and ontologies for governance, AI enablement, and measurable value across BI, ML, and LLM workflows.

Qualifications

• 10+ years of data, metadata, and reference data experience.
• Experience building enterprise glossaries, domain models, and ontologies.
• Experience with data governance, data quality, lineage, and metadata management.
• Ability to establish metadata governance functions, policies, and controls.
• Strong data governance storytelling to drive stakeholder adoption.
• Hands-on with Enterprise Data Catalogs (Alation or equivalent) and curation workflows.
• Understanding how semantic models enable AI/LLM use cases like search and QA.
• Business acumen linking data to process drivers and performance.
• Collaborative delivery across data, analytics, and technology teams.
• Strategic ability to translate objectives into actionable plans.

Responsibilities

• Lead 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 semantic models that make enterprise data AI-ready for BI, ML, and LLM 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.
• Provide authoritative guidance on semantic conflicts and cross-domain dependencies.
• Contribute to the enterprise data product framework with domain boundaries and contracts.
• Document prioritized metadata elements for key processes and AI workflows.
• Identify simplification opportunities to reduce redundancy and improve trust and reusability.
• Partner with analytics, data science, and AI teams to support explainable, governed AI.
• Shape governance strategy and roadmaps as a trusted thought partner.

Skills

Governance storytelling

Strategic thinking

Cross-functional collaboration

Business acumen

Tools

Alation

Collibra

Microsoft Purview

DataHub

Neo4j

Stardog

Amazon Neptune

Azure Cosmos DB

Job description

JOB DESCRIPTION

The AI-Ready Context Engineer/ Ontologist 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 Context Engineer/ Ontologist 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.

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: 09/28/2026

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 [e-mail].