Knowledge Graph & Computational Ontology Engineer (H/F)

SLB is seeking a Computational Ontology & Knowledge Graph Engineer to build the semantic infrastructure powering the next generation of industrial AI. You will design and scale enterprise ontologies and knowledge graphs, transforming complex business and engineering knowledge into trusted, machine-readable models that enable AI systems to reason more accurately and reliably. Key responsibilities: Build and maintain ontologies and knowledge graphs using OWL, RDF, RDFS, SKOS & SHACL Implement graph solutions with SPARQL, Cypher/GraphQL and platforms such as Neo4j, GraphDB, Neptune or Stardog Develop ETL/data pipelines to integrate structured and unstructured enterprise data Partner with domain experts, AI researchers and data scientists to model business knowledge and relationships Ensure ontology quality, consistency, scalability and integration with enterprise data platforms, APIs and digital twins

We are seeking a profile with technical skills in 1. Knowledge representation languages: OWL (Web Ontology Language), RDF/RDFS, SKOS, SHACL 2. Ontology design methodologies: BFO (Basic Formal Ontology), or GFO (General Formal Ontology), ontology design patterns, upper/mid-level ontology reuse (e.g., DOLCE, GIST, IOF — Industrial Ontology Foundry) 3. Reasoning & logic: Description Logic fundamentals, reasoners (Pellet, HermiT, RDFox), consistency checking, inference rules (SWRL) 4. Ontology authoring tools: TopBraid Composer, WebProtégé 5. Knowledge Graph Engineering: a. 1. Query languages: GraphQL (Mandatory), SQL, SPARQL b. Graph database platforms: familiar with both LPG and Triplet Store graph, with experience in at least one graph platform ex: Neo4j, GraphDB (Ontotext), Palantir foundry or Stardog c. Graph data modeling: property graphs vs. RDF triple modeling, schema design for scale d. Data Engineering & Integration: ETL/mapping tools: R2RML, RML, custom Python-based transformation pipelines e. Data integration: mapping relational/enterprise data (SAP, PLM, MES, CMMS) into semantic models (nice to have) The candidate should have excellent communication, analytical and critical thinking skills