Ontology Engineer

The Talent Mine is recruiting an Ontology Engineer for an immediate FTE in-office position in Dallas, Texas. The client is the technology division of North America's largest recycler and leads the steel industry in minimizing environmental impacts, with an unmatched track record of employee investment and stability. The technology division develops and delivers enterprise technology solutions that enable the client's mills and business units to operate safely, efficiently, and competitively.

The Ontology Engineer will be a key contributor to the client's AI & Emerging Technology team, responsible for designing semantic data models, ontologies, and knowledge graphs that serve as the connective tissue between raw operational data and AI-ready intelligence.

• Design, build, and maintain enterprise ontologies and knowledge graphs using standards such as OWL, RDF, and SPARQL.
• Collaborate with domain experts, data engineers, and business stakeholders to capture and formalize business concepts, relationships, and rules.
• Develop and manage taxonomies, controlled vocabularies, and semantic metadata schemas across Nucor's operational and business domains.
• Integrate ontological structures with enterprise data platforms, AI/ML pipelines, and analytics environments.
• Partner with AI/ML Engineers and data scientists to ensure ontology structures support downstream model training, feature engineering, and inference pipelines.
• Define and enforce data governance standards for entity definitions, lineage tracking, and metadata management across enterprise platforms.
• Monitor ontology performance and usage patterns; proactively identify gaps and drive continuous improvement.
• Support integration of ontology layers with enterprise data products, dashboards, and reporting tools.
• Evaluate and implement ontology management tools and platforms, ensuring scalability and interoperability.
• Translate complex technical concepts into clear documentation for both technical and non-technical audiences.
• Stay current with advancements in knowledge representation, semantic web technologies, and AI/ML techniques.

• 3+ years of experience in ontology engineering, knowledge graph development, or semantic data modeling.
• Strong proficiency in OWL, RDF, RDFS, SPARQL, and related W3C semantic web standards.
• Hands‑on experience with ontology development tools such as Protégé, Top Braid Composer, or similar.
• Demonstrated ability to collaborate with cross‑functional teams to model complex business domains.
• Experience with graph databases (e.g., Neo4j, Amazon Neptune, Azure Cosmos DB for Gremlin) and graph query languages.
• Strong understanding of data governance, metadata management, and master data management (MDM) principles.
• Experience collaborating in cross‑functional Agile or Dev Ops environments.
• Excellent analytical thinking with ability to translate ambiguous business requirements into formal semantic models.
• Strong written and verbal communication skills, with ability to present technical concepts to diverse audiences.
• Bachelor's degree in Computer Science, Information Science, Knowledge Engineering, or a related field (or equivalent experience).

• Engineering and Technology:
  Knowledge of the practical application of engineering.
• Science and technology:
  Applying principles, techniques, procedures, and equipment to work at hand.
• Initiative:
  Being proactive with seeking out work that needs to be done and being willing to take on responsibilities and challenges.
• Innovation:
  Introducing new ideas for the continuous improvement of the work area.
• Organizing, Planning, and Prioritizing Work:
  Developing specific goals and plans for prioritizing, organizing, and accomplishing individual work and/or the work of the team.
• Problem Solving & Judgment/Decision Making:
  Identifying problems, gathering and reviewing relevant information, and weighing options to make informed decisions and take effective action.
• Teamwork:
  Working as part of a coordinated effort with others to achieve a common goal.

• Master's degree or Ph.D. in Knowledge Engineering, Computational Linguistics, Computer Science, or related…