Why This Role Stands Out
This role offers a significant opportunity to shape the future of AI at a leading company by architecting a groundbreaking federated knowledge graph. You'll thrive here if you're a seasoned ontology and AI expert eager to drive innovation and build a robust semantic foundation for next-generation products. Apply to make a tangible impact and advance your career in a collaborative environment.
Quick Overview
Job Description
Senior Ontology & Knowledge Graph AI Architect - URGENT
Location: Onsite/Hybrid-New York
Visa: /
Role Summary:
Pearson is seeking a highly experienced Ontology & AI Expert to design and accelerate the development of a federated enterprise knowledge graph ("knowledge graph of knowledge graphs") that connects learner, assessment, skills, workforce, and content data domains. This strategic initiative will establish an AI-ready semantic foundation to power next-generation products, insights, and LLM-driven experiences.
Key Responsibilities
- 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.
Required Qualifications
- 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.
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