# Harnham — Director, Ontology & Knowledge Products

- Generated: 2026-09-02 09:34:05 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4462092598/
- Provider: linkedin
- Posting time: approximately 2026-09-01 08:34 PM EDT (estimated from provider's '13 hours ago' at capture)
- Applicants: Be among the first 25 applicants
- Work model/location: Fully remote; Massachusetts is eligible.; provider location: United States
- Compensation: Approximately $265K target, maximum $300K, plus 20% bonus; qualifies.
- Travel: Occasional travel to Dallas; percentage not disclosed, so not failed.
- Positioning track: Technical Manager
- Fit outcome: BORDERLINE — 72.2%

## Direct-match strengths

Differentiated ontology and knowledge-graph history, healthcare/life-sciences domain, recent RAG/vector work, and greenfield leadership.

## Hard or material gaps

Recent enterprise ontology portfolio ownership, formal lifecycle/versioning, and clearly documented 8-12 years of ontology-focused responsibility are weak; no Palantir.

## Evidence map

1. Enterprise ontology strategy (w3/e2): BioWizard/UMLS and Ingenuity knowledge systems are direct but old.
2. Semantic modeling/taxonomy/metadata (w3/e2): Bioinformatics knowledge discovery plus enterprise metadata/catalog work.
3. Knowledge graph/graph database (w3/e3): Built Dun & Bradstreet's first Neptune graph database.
4. AI use cases to ontology (w3/e2): BioWizard, IPA, RAG, and agents; modern enterprise ownership is less explicit.
5. Product lifecycle/governance (w2/e2): Strong product and governance leadership; ontology versioning is not directly documented.
6. Hands-on Director/greenfield build (w2/e3): Repeated player-coach and function-building evidence.
7. Regulated health/life sciences (w2/e3): Ph.D., genomics, pharma, bioinformatics, HIPAA, and healthcare platforms.
8. 8-12 years ontology work (w3/e1): Aggregate historical experience may qualify, but chronology and recency are unclear.
9. AI-ready retrieval/vector context (w2/e3): RAG, PGVector, embeddings, UMLS, and Neptune.
10. Palantir Foundry (w1/e0): No evidence; preferred only.

## Full normalized job description

Director, Ontology & Knowledge Products
Location:
Fully Remote, with occasional travel to Dallas, TX
Restricted States:
Candidates cannot work from California, New York, Hawaii, North Dakota, Oregon, Rhode Island, Washington, or Wyoming
Work Authorization:
U.S. Citizens and Green Card holders only
Base Salary:
Target of approximately $265,000, with a maximum of $300,000
Bonus:
20% annual bonus
Benefits:
Healthcare, 401(k), and comprehensive benefits
The Opportunity
We are partnering with a large, complex healthcare organization making a significant investment in AI, agentic AI, and consumer-facing digital experiences.
The
Director of Ontology & Knowledge Products
will build the enterprise ontology and semantic products required to support AI use cases, analytics, operational workflows, and knowledge-enabled digital experiences.
This is a
greenfield opportunity
. The ontology function does not exist today, and this leader will help design the capability, operating model, roadmap, and team from the ground up.
What You'll Do
Ontology Strategy & Design
Own the enterprise ontology portfolio and semantic product strategy across priority AI use cases.
Translate business, clinical, operational, analytics, and AI needs into an ontology roadmap, backlog, and delivery plan.
Lead ontology design across enterprise domains, including entities, relationships, attributes, definitions, business rules, and cross-domain mappings.
Define semantic modeling standards supporting AI reasoning, retrieval, analytics, and knowledge graphs.
Build reusable ontology capabilities that extend across multiple enterprise use cases.
Ontology Lifecycle & Data Products
Own ontology products from discovery and design through implementation, validation, adoption, monitoring, and refinement.
Establish change management, versioning, documentation, governance, and support processes.
Align data product roadmaps with ontology priorities to ensure enterprise data is reliable, semantically consistent, and AI-ready.
Resolve cross-domain definition, quality, prioritization, and ownership issues.
Governance & Cross-Functional Leadership
Partner with Data Governance, Data Architecture, Data Engineering, AI Product, AI Engineering, Security, Privacy, and business and clinical stakeholders.
Align ontology standards, data definitions, metadata, stewardship, and data quality practices.
Serve as the primary ontology leader for AI use-case teams.
Communicate ontology priorities, design decisions, tradeoffs, risks, and progress to senior leadership.
Help establish and scale the long-term ontology and knowledge products function.
What We're Looking For
Proven experience leading
ontology, semantic layer, knowledge graph, metadata, or enterprise information architecture
work in a complex organization.
Deep understanding of semantic modeling, entity/relationship design, taxonomy, metadata, data definitions, and knowledge graph enablement.
Experience translating AI use cases into ontology and semantic product requirements.
Experience building reusable enterprise data or knowledge capabilities rather than isolated solutions.
Strong product ownership experience across roadmaps, prioritization, lifecycle management, and stakeholder alignment.
Ability to remain
deeply technical and hands-on
while operating at a Director level.
Experience working across complex, highly matrixed organizations.
Experience
14–18 years of overall experience across data, ontology, semantic modeling, enterprise information architecture, knowledge management, data products, governance, or related areas.
8–12 years involving ontology, semantic layers, taxonomy, metadata, knowledge graphs, enterprise data, or information architecture.
5–8+ years of leadership experience across teams, major programs, product portfolios, or enterprise data/knowledge initiatives.
Experience designing, operating, or scaling ontology, semantic models, knowledge graphs, metadata, or data product capabilities.
Healthcare, life sciences, financial services, or another complex regulated-industry background is strongly preferred.
Technical Expertise
Ontology design and semantic modeling
Enterprise taxonomy and metadata management
Entity/relationship modeling and knowledge architecture
Knowledge graphs and graph databases
Semantic layers and retrieval patterns
Data catalogs and modern enterprise data platforms
AI-ready data, retrieval augmentation, embeddings/vectorization, and governed context management
Privacy, security, compliance, and responsible AI
Preferred Qualifications
Experience
building an enterprise ontology, semantic layer, knowledge graph, or knowledge product capability from scratch
.
Experience supporting AI, GenAI, conversational AI, search, personalization, decision-support, or workflow automation.
Experience with healthcare data domains such as patients, providers, scheduling, encounters, medications, claims, billing, or clinical documentation.
Experience with graph/semantic technologies, data catalogs, metadata management, MDM, or AI knowledge/retrieval systems.
Experience with
Palantir Foundry or similar ontology-driven enterprise platforms
is highly valuable

## Artifact metadata

- Resume and cover letter: Not generated under the fit gate.
- Archived JD capture: https://files.keithsteward.com/Harnham_Ontology/Keith_Steward_director-ontology-and-knowledge-products_4462092598_JD_capture.md
- Google Drive used: No