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Ontology Specialist, Coverage Intelligence

Job in Dublin, Franklin County, Ohio, 43016, USA
Listing for: Bold Penguin
Full Time position
Listed on 2026-10-30
Job specializations:
  • IT/Tech
    Information & Knowledge Management, AI Evaluation, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
YOUR ROLE

As the Ontology Lead on the Coverage Intelligence team, you own the formal knowledge model that our AI systems use to understand insurance coverage inside the Digital Exchange, powered by DeX ai. You’ll take an ontology framework already in use and evolve it into a governed, scalable model that engineers can build on and agents can reason against consistently and explain ably.

You set the standard for how insurance knowledge is represented, working closely with our coverage specialist, who brings deep coverage and legal expertise, and with the AI and data engineers who carry the model into production. This role suits someone who has built and governed ontologies in a complex, language-heavy domain, ideally legal or insurance, and who enjoys making expert knowledge precise.

Brief

Description

As the Ontology Lead on the Coverage Intelligence team, you own the formal knowledge model that our AI systems use to understand insurance coverage inside the Digital Exchange, powered by DeX ai. You’ll take an ontology framework already in use and evolve it into a governed, scalable model that engineers can build on and agents can reason against consistently and explain ably.

You set the standard for how insurance knowledge is represented, working closely with our coverage specialist, who brings deep coverage and legal expertise, and with the AI and data engineers who carry the model into production. This role suits someone who has built and governed ontologies in a complex, language-heavy domain, ideally legal or insurance, and who enjoys making expert knowledge precise.

What

You'll Do
  • Take ownership of our existing coverage ontology and evolve it into a governed, scalable model of concepts, relationships, taxonomies and rules.
  • Serve as the authority on the model of record, making final decisions on what concepts mean and how they relate, in partnership with the engineers who implement it.
  • Partner with coverage experts to capture how policies are read and interpreted, and represent that knowledge accurately and consistently.
  • Establish governance for the ontology as a living asset, including versioning, change control and quality standards.
  • Work with data and AI engineers to carry the ontology into schemas, data contracts and agent reasoning, keeping the product aligned with the model of record.
  • Align the model with existing enterprise data dictionaries and industry standards so that concepts stay consistent across products.
  • Measure the model’s quality by how well it supports accurate extraction, classification and coverage analysis, and refine it based on evidence.
  • Extend the model as new lines of business, document types and use cases are added, from standard forms to non-standard and bespoke wording.
  • Help the wider team understand and use the ontology, so knowledge does not depend on one person.
  • Other duties and responsibilities as assigned.
YOUR LOCATION

This is a fully remote role, with the exception of onboarding and optional in-office events.

Skills And Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Information Science, Linguistics or a related field, or equivalent experience.
  • 5+ years’ experience designing and maintaining ontologies, taxonomies or knowledge graphs in production, not just at launch.
  • Strong command of knowledge representation, from formal standards (OWL, RDF, SKOS, SHACL) to schema-based models (JSON Schema, typed data models) and property graphs, and the judgment to choose between them.
  • Experience eliciting knowledge from subject matter experts and translating it into precise, testable structure.
  • Experience governing a model over time, including versioning, change management and backward compatibility.
  • Comfortable working hands-on with data models and schemas…
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