Basic Qualifications
Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus a minimum of 6 years of relevant experience. CLEARANCE REQUIREMENTS: : Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position
What You'll Own
- Domain ontologies. Design and maintain semantic schemas that describe key engineering and manufacturing entities — products, BOMs, plants, equipment, processes, work orders — and their relationships across systems.
- Knowledge graphs. Implement ontologies using semantic web or graph technologies (RDF/OWL/SHACL/SPARQL or property-graph equivalents like Neo4j). Build, query, validate, and tune knowledge graphs in production.
- Data alignment. Integrate heterogeneous data sources — PLM, ERP, MES, CMMS, QMS, data lakes — into a common vocabulary. Align schemas, code sets, and master data to the ontology so AI services see one coherent picture.
- Semantic layer. Design the enterprise semantic layer that BI tools, analytics platforms, and AI/LLM applications query consistently. Define core business entities, metrics, and hierarchies and map them to existing data stores.
- Ontology governance. Manage versioning, documentation, reuse of industry standards, and enforcement of modeling best practices across pods. Your ontologies are shared assets — they must be maintainable by others.
What You Won't Own
- AI model development or prompt engineering — you provide the data substrate, the AI engineers build on it
- Enterprise system administration — you integrate data from systems, you don't manage them
- Business process decisions — Domain SMEs and the Product Owner define what matters; you model it
What Makes This Role Different
- Your ontologies directly feed AI systems that make real business decisions. A bad data model doesn't just slow a report — it makes an AI agent reason incorrectly.
- You will work across multiple enterprise domains — HR, manufacturing, CRM, supply chain — building a shared knowledge architecture, not siloed data models.
- You will collaborate with business SMEs who understand the domain and AI engineers who consume your models. You translate between both worlds.
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, Information Science, or a related field, plus 5 years of experience; or Master’s degree plus 3 years of experience
- Hands