Ontology Engineer

Role Description

We are seeking a highly skilled Ontology Engineer to design, develop, and maintain semantic knowledge models that enable intelligent data integration, interoperability, and AI-driven applications. The ideal candidate will have expertise in semantic web technologies, ontology development, and knowledge graph design, with the ability to collaborate across business and technical teams to create machine-interpretable data models. This role will play a key part in improving AI-powered systems by structuring enterprise knowledge, reducing AI hallucinations, and enhancing information retrieval through well-defined ontologies and semantic standards.

Key Responsibilities

• Design, develop, and maintain enterprise ontologies using semantic web standards and best practices.
• Build and manage formal knowledge frameworks to ensure data is machine-readable and interoperable.
• Map proprietary business terminology and internal data models to industry-standard ontologies and reference models.
• Develop semantic models that enable seamless data integration across systems and departments.
• Collaborate with AI engineers and data scientists to structure knowledge for AI, machine learning, and knowledge graph applications.
• Improve AI performance by creating high-quality semantic models that reduce hallucinations and improve contextual information retrieval.
• Gather and translate competency questions from product managers, UX designers, and subject matter experts into scalable ontology models.
• Design and maintain taxonomy structures, controlled vocabularies, and metadata standards.
• Create documentation for ontology design, governance, and maintenance processes.
• Ensure ontology quality, consistency, scalability, and compliance with organizational data governance standards.
• Support knowledge graph implementation and semantic search initiatives.

Qualifications

• Semantic Web Technologies
• Strong expertise in:
  • RDF (Resource Description Framework)
  • RDFS
  • OWL (Web Ontology Language)
  • SPARQL
• Deep understanding of semantic data modeling and linked data principles.
• Ontology Development Tools
• Hands-on experience with one or more of the following:
  • Protégé
  • TopBraid
  • Composer
  • PoolParty
  • CENtree
  • Other ontology or taxonomy management platforms
• Technical Skills
• Proficiency in Python for scripting, automation, and ontology processing.
• Experience working with:
  • JSON
  • XML
  • Turtle (TTL)
  • RDF serialization formats
• Familiarity with APIs and data integration workflows.
• Understanding of knowledge graph technologies is highly desirable.