Knowledge Architecture Lead / Senior Ontologist

Accenture•Mountain View, CA

1d•$138,800 - $413,600•Hybrid

About The Position

We are seeking a Senior Ontologist and Knowledge Architecture Lead 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.

Requirements

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.

Responsibilities

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
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
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
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
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
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)