Sr. Taxonomy & Ontology Architect

About ISACA

ISACA® (www.isaca.org) champions the global workforce advancing trust in technology. For more than 55 years, ISACA has empowered its community of 195,000+ members with the knowledge, credentials, training and network they need to thrive in fields like information security, governance, assurance, risk management, data privacy and emerging tech. With a presence in more than 195 countries and with more than 230 chapters worldwide, ISACA offers resources tailored to every stage of members’ careers—helping them to thrive in a rapidly changing digital landscape, drive trusted innovation and ensure a more secure digital world. Through the ISACA Foundation, ISACA also expands IT and education career pathways, fostering opportunities to grow the next generation of technology professionals.

Overview

The Sr. Taxonomy & Ontology Architect serves as a senior technical resource for taxonomy, ontology, metadata, and knowledge graph architecture, providing technical guidance and recommendations for the design, implementation, governance, and ongoing improvement of ISACA’s knowledge ecosystem. The role contributes to and applies standards, frameworks, and architectural direction that enable knowledge assets to be consistently structured, connected, discovered, and leveraged across ISACA’s products, platforms, content experiences, and AI-enabled solutions. The Architect supports the development and maintenance of the knowledge architecture roadmap, helping enhance interoperability across systems and improve search, personalization, content reuse, and scalable digital experiences for members and customers worldwide.

Responsibilities

Enterprise Taxonomy, Ontology, and Knowledge Graph Architecture

Design, maintain, and improve ISACA’s taxonomy, ontology, metadata, and knowledge graph architecture practices and solutions. Serve as a senior technical resource for semantic modeling and knowledge representation, utilizing Graphwise Graph Modeling, GraphDB, and human-in-the-loop review methodologies to support the accuracy, scalability, governance, and business relevance of knowledge assets. Contribute to standards, frameworks, and roadmap planning that support AI-powered discovery, content interoperability, personalization, and knowledge reuse across ISACA’s digital ecosystem.

Knowledge Graph Architecture and AI Enablement

Support the design, implementation, and optimization of knowledge graph capabilities leveraging Graphwise Graph Modeling, GraphDB, GraphRAG, semantic standards, and human-in-the-loop validation practices. Partner with AI architects, engineers, product leaders, and other stakeholders to ensure knowledge assets are structured and governed for effective use in search, retrieval, recommendation, personalization, and emerging AI-enabled applications. Contribute to the ongoing evolution of semantic AI capabilities by applying technical expertise, evaluating solution performance, and recommending improvements that strengthen knowledge graph usability and business value.

Cross-Functional Architecture Leadership

Provide technical guidance and collaborate with content, product, technology, UX, and data stakeholders to support effective knowledge architecture practices. Inform platform requirements, content architecture, integration approaches, and semantic technology decisions to support cross-functional initiatives and business objectives. Translate taxonomy, ontology, metadata, and knowledge graph concepts into clear recommendations that help teams implement consistent, scalable, and user-centered solutions.

Data Integration, Classification, and Semantic Governance

Support and guide the evaluation, normalization, mapping, classification, and integration of internal and third-party knowledge assets. Apply and help improve governance processes that incorporate human-in-the-loop review to validate automated tagging, ontology expansion, content classification, and semantic enrichment activities. Ensure consistency, interoperability, and quality across content and data sources through hands-on analysis, documentation, stakeholder collaboration, and adherence to established governance practices.

Performance Optimization and Continuous Improvement

Analyze knowledge platform analytics, search behavior, retrieval performance, and content utilization trends to identify opportunities for improving discoverability, relevance, taxonomy effectiveness, and knowledge architecture maturity. Recommend practical enhancements to taxonomy, ontology, metadata, and knowledge graph structures based on performance data, stakeholder feedback, and evolving business needs.

Knowledge Architecture Governance and Organizational Capability Development

Serve as a senior technical resource on taxonomy, ontology, knowledge graphs, semantic technologies, Graphwise Graph Modeling, GraphDB, and human-in-the-loop knowledge engineering practices. Provide guidance, documentation, and knowledge-sharing support to stakeholders to promote consistent use of knowledge architecture standards and practices. Contribute input on relevant tools, technologies, and industry practices, and recommend improvements that support ISACA’s knowledge architecture maturity and AI-enabled capabilities.

Qualifications

Required Field of Study

BA/BS, Library Science, Data or Information Science, computer science, Computational Linguistics, Digital Humanities, English, Communications or related area

Minimum Years of Experience Required

8+ years of progressive experience in taxonomy, ontology, metadata, information architecture, content architecture, knowledge management, semantic modeling, or related knowledge architecture disciplines, including hands-on experience designing, implementing, and supporting governance of structured knowledge assets in complex digital content, search, data, or AI-enabled environments.

Description of Minimum Experience Required

• Progressive experience designing, implementing, and supporting governance of taxonomies, ontologies, metadata models, knowledge graphs, and semantic architectures within complex content, knowledge management, search, or AI-enabled environments.
• Advanced experience using LLM-assisted and automated methods for taxonomy/ontology development and content classification, with human-in-the-loop review.
• Advanced hands-on experience with Graphwise Graph Modeling, GraphDB, Semantic Analytics, Graph Automation, GraphRAG, PoolParty, and human-in-the-loop review methodologies, including applying and contributing to governance standards and evaluation frameworks for semantic enrichment, automated classification, and knowledge graph development.
• Deep understanding of semantic web and knowledge representation standards, including SKOS, RDF, OWL, and SPARQL, with demonstrated experience applying these technologies to complex knowledge architecture initiatives.
• Experience supporting the architecture, implementation, and governance of knowledge graph initiatives, including evaluation and optimization of automated tagging, classification, entity extraction, semantic enrichment, and retrieval methodologies through both machine learning and symbolic AI approaches.
• Proven ability to collaborate with cross-functional teams and partner with AI architects, search engineers, application developers, UX professionals, product leaders, and business stakeholders to support information architecture standards, semantic strategies, and platform requirements.
• Experience evaluating, adapting, and supporting governance of industry-standard taxonomies and ontologies, such as NICE, ESCO/O*NET, and related frameworks, including content mapping, semantic normalization, and integration of legacy and third-party knowledge assets into machine-readable knowledge structures.
• Demonstrated ability to communicate and support content architecture, content intelligence, and semantic enrichment approaches across complex technology ecosystems and content supply chains.
• Proven success