Knowledge Architecture Lead / Senior Ontologist

We Are:

Accenture is a global professional services and solutions company that helps leading organizations reinvent with digital, cloud, data, and AI capabilities, drawing on its large global workforce, industry expertise, and ecosystem partnerships to create 360° value.

By combining hands-on engineering with deep industry context, we help organizations build their digital core, modernize operations, unlock value from data and AI, and deliver tangible business outcomes at speed and scale.

You Are:

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.

Key Responsibilities:

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. Travel can be between 20-80%