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ISACA

Senior Taxonomy & Ontology Architect

Data ManagementUpdated on Nov 10
Full-timeRemote in USA$104.2k - $156.3k /yr

About the Job

Requirements

  • A BA/BS or degree in Library Science, Data or Information Science, Computer Science, Computational Linguistics, Digital Humanities, English, Communications, or a related area is required.
  • At least 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.
  • 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 and 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 machine learning and symbolic AI approaches.
  • 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 and ESCO/O*NET, including content mapping, semantic normalization, and integration of legacy and third-party knowledge assets into machine-readable knowledge structures.
  • Ability to communicate and support content architecture, content intelligence, and semantic enrichment approaches across complex technology ecosystems and content supply chains.
  • Success balancing longer-term architectural considerations, governance requirements, and knowledge maturity goals with near-term product milestones, business priorities, and MVP delivery requirements.
  • Ability to anticipate, analyze, and resolve complex challenges affecting content reuse, discoverability, interoperability, and knowledge governance while supporting alignment across multiple stakeholder groups and platforms.
  • Excellent written and verbal communication skills, with strong knowledge of English grammar, spelling, and punctuation.
  • Ability to function effectively in a collaborative environment and as a strong individual contributor.
  • Strong organizational skills, attention to detail, and ability to manage multiple projects with varied priorities and deadlines simultaneously.

Responsibilities

  • Design, maintain, and improve the organization’s taxonomy, ontology, metadata, and knowledge graph architecture practices and solutions.
  • Serve as a senior technical resource for semantic modeling and knowledge representation, using Graphwise Graph Modeling, GraphDB, and human-in-the-loop review methodologies to support 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 the digital ecosystem.
  • Support the design, implementation, and optimization of knowledge graph capabilities using 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 evolution of semantic AI capabilities by applying technical expertise, evaluating solution performance, and recommending improvements that strengthen knowledge graph usability and business value.
  • 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.
  • Support and guide evaluation, normalization, mapping, classification, and integration of internal and third-party knowledge assets.
  • Apply and help improve governance processes incorporating 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.
  • Analyze knowledge platform analytics, search behavior, retrieval performance, and content utilization trends to identify opportunities to improve 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.
  • 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 knowledge architecture maturity and AI-enabled capabilities.
  • Attend onsite periodically, currently or in the future, based on business needs, and travel occasionally for company-sponsored events, meetings, all-hands gatherings, training sessions, or other activities necessary to support the role.

Desired Qualifications

  • An advanced degree in library, data, or information science; computer science; computational linguistics; knowledge engineering; or a related discipline is preferred.
  • At least 10 years of progressively responsible experience supporting taxonomy, ontology, metadata, knowledge graph, or semantic architecture initiatives, including contributing to standards, collaborating with cross-functional technology and product teams, supporting governance of knowledge ecosystems, and enabling search, personalization, content interoperability, or AI-driven knowledge applications.
  • A knowledge management, taxonomy, ontology, or semantic architecture certification is a plus.
  • International experience and/or non-English language competency, such as Spanish, Japanese, or Chinese, is a plus.
  • Nonprofit, professional association, or volunteer engagement experience is a plus.
  • Experience participating in Agile programs or projects, especially those involving content supply chain improvement, platform implementation, or content operations.
  • Familiarity with architecture and development concepts and terminology, including application modeling, object-oriented concepts, APIs, integration patterns, and structured data.
  • Familiarity with content standards, including XML, DITA, JSON, and HTML, and semantic standards such as SKOS, RDF, and OWL.
  • General familiarity with content scripting languages and approaches, including XSLT, CSS, Python, or related tools.
  • Coursework or applied experience in application development, content architecture, information architecture, data architecture, or scripting languages.
  • Vendor management experience is a plus.
  • Experience with data/information architecture, content analytics and enrichment, content conversion, and search/discovery optimization is a plus.
  • AI/machine learning certifications are preferred.

About the Company

Company size
Not listed
Company stage
Not listed
Total funding
Not listed
Headquarters
Schaumburg, IL
Founded
1969

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