Ontology - Knowledge Graph Specialist

Job Title: Ontology / Knowledge Graph Specialist

Location: Southlake, TX (Hybrid - 2 Days Onsite at Client Location)

Employment Type: Contract

Domain: Telecom - Network Automation & AI

Role Summary:

We are seeking a Hands-on Ontology / Knowledge Graph Engineer to design, build, and maintain enterprise-grade knowledge models that power network automation, semantic search, and AI/Agentic systems. This is a highly technical, hands-on role for someone who can bridge deep Semantic Web expertise (RDF/OWL/SHACL) with practical data engineering and real-world telecom/network domain modeling. You will work directly with Network SMEs to convert implicit, complex business knowledge into explicit, validated, and reusable semantic models.

Key Responsibilities:

1. Ontology Design & Modeling

• Design, build, and evolve enterprise ontologies using RDF, RDFS, OWL, Turtle (TTL), and SHACL
• Create robust class/property hierarchies, taxonomies, namespaces, relationships, and reusable ontology design patterns
• Apply both schema-first and schema-late modeling approaches, including reverse-engineering ontologies from existing datasets

2. Data Profiling & Knowledge Graph Engineering

• Profile, analyze, and model large, complex, and messy datasets from Excel/CSV, CIQ, Network Config, Inventory/CMDB, JSON, and Relational sources
• Define atomic vs. derived attributes, cross-field relationships, deterministic derivation rules, and validation logic
• Develop SPARQL 1.1 queries, competency questions, graph traversals, and dependency/impact analysis

3. Platform & Pipeline Development

• Build and maintain ontology ingestion, transformation, validation, and testing pipelines using Python
• Work with RDF Triple Stores like Graph DB, Star dog and have working knowledge of Labeled Property Graph (LPG) platforms like Neo4j
• Implement versioning, documentation, and testing for all ontology artifacts in Git / CI/CD

4. AI & Stakeholder Integration

• Enable Ontology-RAG / Graph RAG / Hybrid (Graph + Vector) retrieval patterns and integrate Knowledge Graphs with AI Agents and LLMs
• Partner closely with Network & Domain SMEs to translate implicit engineering knowledge into explicit, testable models
• Own ontology documentation, specifications, data mappings, and SHACL validation rules

Required Skills & Experience:

• 5+ Years of hands-on experience in Ontology Engineering / Knowledge Graphs
• Expert-level proficiency in RDF, RDFS, OWL, TTL, SHACL, SPARQL, and Semantic Web Standards
• Strong experience with RDF Graph Databases (Graph DB / Star dog) and understanding of LPGs (Neo4j)
• Proven experience with schema-first & schema-late development and reverse-engineering data models
• Strong data modeling skills - JSON Schema, Relational Modeling, and mapping Relational/JSON -> Graph
• Proficiency in Python for building data pipelines (rd flib, Py SHACL, pandas preferred)
• Experience working with messy, incomplete, large-scale enterprise data
• Excellent communication skills to work with technical and business stakeholders

Preferred / Nice-to-Have:

• Telecom domain experience - Network Inventory, CMDB, Network Configuration, Service Modeling
• Experience with Graph RAG, Vector DBs (Pinecone, Weaviate, Milvus), and LLM Agent frameworks (Lang Chain, Llama Index)
• Knowledge of SKOS, Ontology Design Patterns, and Linked Data principles
• Experience with Data Governance and Metadata Management