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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Knowledge Architecture Lead / Senior Ontologist - **Company:** Accenture - **Location:** Arlington, VA, United States - **Experience:** Expert - **Salary:** $163,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Application Integration Architecture, Information Engineering, Data Governance, Data Structures, Middleware, Graph Database, Information Extraction, Information Sciences, Modular Design, Named Entity Recognition, Web Ontology Language, Resource Description Framework (RDF), Semantic Web, Management of Software Versions, Feature Engineering, Knowledge Representation, Integration Tests, Information Technology, Machine Learning Operations, Software Version Control - **Published:** August 7, 2026 - **Apply:** https://dejobs.org/x/x/4EBE71FB7F884E21992DCABBD2F61E36/job/ ## About the Role * Minimum 12 years years of hands-on experience in ontology engineering, knowledge modeling, or a closely related semantic web or knowledge representation discipline * Minimum 12 years previous experience owning and delivering production-grade domain ontologies in complex enterprise or large-scale consulting environments including working in Agile or iterative delivery environments, * Minimum 12 years experience in a lead, principal, or architect-level role with responsibility for technical standards, team development, and roadmap ownership and stakeholder-facing estimation, * Bachelor's or Master's degree (or PhD) in Information Science, Computer Science, Library Science, Linguistics, Philosophy, or a related field. ## Description to own the design, governance, and delivery of enterprise knowledge graph initiatives. This role carries the principal responsibilities for developing and implementing semantic modeling strategy, ontology governance frameworks, and the technical direction of a cross-functional team spanning business stakeholders, data engineering, and AI/ML disciplines., Ontology Strategy & Architecture: * Own the end-to-end ontology lifecycle: requirements gathering, conceptual modeling, formal specification (OWL 2, RDFS, SKOS), validation, deployment, and long-term stewardship * Define enterprise ontology architecture: modular design patterns, URI strategy, versioning policy, and alignment with upper ontologies (e.g., BFO, DOLCE, schema.org) * Establish T-Box design standards and govern A-Box hydration patterns across structured and unstructured data sources * Make authoritative decisions on advanced modeling patterns (e.g., reification, n-ary relations, punning, ontology modularization) and document rationale for organizational reuse * Lead alignment efforts between domain ontologies and enterprise-wide or cross-domain semantic assets * Evaluate and recommend the selection of ontology tooling, triplestore platforms, and semantic middleware to meet project and organizational requirements Ontology Design & Development: * Author and review ontologies, taxonomies, and vocabularies using OWL, RDF, RDFS, and SKOS to production-quality standards * Define and enforce competency question frameworks to scope, drive, and validate ontology design across delivery workstreams * Lead mapping of traditional data structures (relational, semi-structured) into semantic frameworks using R2RML, RML, or equivalent * Oversee knowledge graph hydration, integration testing, and validation pipelines * Ensure ontological models align with business goals, regulatory requirements, and enterprise data governance policies Governance & Standards: * Establish and own ontology governance standards: version control protocols, change management processes, quality gates (W3C compliance, SHACL/ShEx validation), and deprecation policies * Define and enforce Definition of Done criteria for all ontology deliverables * Lead ontology review and approval processes, including peer review structures and sign-off with business and technical stakeholders * Maintain and evolve governance documentation, modeling guidelines, and pattern libraries for use across the team Stakeholder Leadership: * Lead business SME workshops to elicit domain concepts, relationships, business rules, and competency questions * Serve as the primary semantic modeling authority for business and technical stakeholders, resolving ambiguity and driving alignment * Translate complex modeling decisions into accessible rationale for non-technical audiences, including senior business sponsors * Represent the knowledge modeling function in cross-organizational planning, architecture review boards, and governance forums Technical Leadership & NLP/AI Integration: * Partner with Entity Extraction and NLP teams to develop ontology-guided pipelines for information extraction from unstructured sources * Advise AI/ML teams on ontology-informed feature engineering, embedding strategies, and knowledge-augmented model design * Define integration patterns between the knowledge graph and downstream analytical, search, and AI/ML systems * Stay current with advances in semantic web, knowledge representation, and neuro-symbolic AI; translate emerging practices into team standards Team Leadership & Delivery Management: * Lead, mentor, and develop a team of ontologists and semantic analysts at intermediate and junior levels * Conduct structured knowledge transfer, design reviews, and coaching to build team capability and modeling maturity * Own delivery timelines, workstream dependencies, and risk escalation across the ontology program * Coordinate across Data Engineering, AI/ML, Product, and Business SME workstreams to ensure coherent delivery * Lead roadmap planning, scope definition, and estimation (T-shirt sizing / story pointing) for ontology initiatives across delivery horizons (v1/v2/v3) This role is hybrid in nature and will require time in office and traveling to client locations. 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