Job Summary
The Ontology / Knowledge Graph Engineer will be responsible for designing, developing, and maintaining enterprise-scale ontologies and knowledge graph solutions. The role requires strong expertise in semantic technologies, ontology engineering, graph databases, and linked data standards to model complex business domains, integrate heterogeneous data sources, and enable semantic search, reasoning, and AI-driven knowledge management.

Key Responsibilities
• Design, develop, and maintain enterprise ontologies and knowledge graph solutions.
• Build semantic data models to represent complex business domains and relationships.
• Develop and optimize RDF-based knowledge graphs using industry standards.
• Create and maintain OWL ontologies, RDF schemas, and SHACL validation rules.
• Develop and optimize SPARQL queries for data retrieval, transformation, and analytics.
• Perform ontology alignment, entity resolution, and semantic data integration.
• Design and implement ontology-driven knowledge graph architectures.
• Implement semantic reasoning capabilities and ontology inference techniques.
• Ensure ontology consistency through validation and inference mechanisms.
• Integrate structured and unstructured data into enterprise knowledge graphs.
• Collaborate with data engineers, solution architects, AI/ML teams, and business stakeholders.
• Optimize graph performance, scalability, and data quality.
• Develop and maintain ontology documentation, semantic standards, and implementation best practices.
• Support semantic search, knowledge management, and enterprise data integration initiatives.

Required Qualifications
• Bachelor's or Master's degree in Computer Science, Information Systems, Artificial Intelligence, Data Science, or a related field.
• Strong experience in ontology engineering and knowledge modeling.
• Expertise with OWL (Web Ontology Language).
• Strong knowledge of RDF (Resource Description Framework).
• Experience writing complex SPARQL queries.
• Experience with SHACL for RDF validation.
• Experience with JSON-LD.
• Strong understanding of ontology inference and semantic reasoning.
• Experience performing ontology consistency checking and validation.
• Experience designing and implementing enterprise knowledge graphs.
• Strong understanding of property graphs and RDF graphs.
• Experience with graph data modeling and graph analytics.
• Experience with ontology-driven knowledge graph design.
• Experience with entity resolution and identity matching.
• Strong knowledge of semantic modeling concepts.
• Experience with semantic technologies and linked data standards.
• Hands-on experience with Protégé.
• Experience with TopBraid Composer and/or OntoStudio.
• Experience working with graph database technologies such as Neo4j, Stardog, GraphDB, Apache Jena, Apache Fuseki, Blazegraph, or Virtuoso.
• Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications
• Experience building enterprise semantic knowledge management platforms.
• Familiarity with Linked Open Data (LOD) principles.
• Experience integrating knowledge graphs with AI/ML, NLP, or Generative AI solutions.
• Understanding of graph algorithms and semantic reasoning engines.
• Experience with AWS, Azure, or Google Cloud Platform (GCP).
• Experience with GraphQL APIs.
• Knowledge of Python or Java for semantic application development.
• Experience with enterprise metadata management and data governance.
• Exposure to Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and semantic search architectures.