Ontology & Knowledge Graph AI Architect

• Design and define an enterprise-wide ontology framework spanning learner, assessment, skills, workforce, and educational content domains.
• Architect and implement large-scale federated knowledge graph solutions integrating multiple existing knowledge graphs and data sources.
• Develop AI/ML-driven approaches for automated ontology creation, entity classification, ontology alignment, relationship discovery, and semantic enrichment.
• Build semantic models, reasoning frameworks, and inference mechanisms to uncover relationships across domains.
• Collaborate with product, data science, engineering, and business stakeholders to establish a reusable AI-ready knowledge layer.
• Lead the initial PoC focused on Learner Skills to Job Skills Mapping, leveraging assessment outcomes, competencies, skills ontologies, and career pathways.
• Provide strategic guidance on enterprise knowledge graph architecture, governance, scalability, and future AI adoption.

• 10+ years of experience in Ontology Engineering, Semantic Technologies, Knowledge Graphs, AI/ML, or Data Science.
• Deep expertise in ontology design, semantic data modeling, taxonomies, RDF, OWL, SKOS, SPARQL, and graph-based architectures.
• Hands-on experience building and managing enterprise-scale knowledge graphs and metadata ecosystems.
• Strong background in Machine Learning, NLP, Generative AI, and automated knowledge extraction/classification.
• Experience with entity resolution, graph embeddings, semantic search, reasoning, and ontology mapping.
• Proficiency with graph databases and semantic platforms such as Neo4j, Stardog, GraphDB, Amazon Neptune, or similar.
• Ability to engage with senior leadership and provide architectural and strategic consulting.

Preferred Experience

• Exposure to learning, education, workforce skills, competency frameworks, or talent intelligence platforms.
• Experience leveraging knowledge graphs to enable LLM and AI-powered applications.