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Job Closed

Senior Ontology & Knowledge Graph AI Architect

  • Source: LinkedIn
  • Cognizant
  • On-site
  • New York City
  • Full-Time
  • Senior

Job Description

Job Title: Senior Ontology & Knowledge Graph AI Architect

Location: Onsite/Hybrid

Role Summary

We are 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.

Skills

  • microsoft-graph
  • neo4j
  • stardog
  • graphdb
  • amazon-neptune
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