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Senior Ontology & Knowledge Graph AI Architect- New York (Hybrid)

Avtech SolutionsNew York, NY🇺🇸United StatesPosted 24 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
New York, NY, United States
Posted
22 hours ago
Neo4jMachine LearningNLPGenerative AILLM

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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