Tech Engineering Manager

Principal Engineer, Knowledge Graph
Data StrategyUS Exempt RegularFull timeStateside Exempt 4.4 Location: Stateside Remote
We are seeking a strategic and technically proficient Principal Engineer, Knowledge Graph to lead the design, development, and implementation of enterprise-grade knowledge graph solutions. This leader will be responsible for driving semantic data modeling, graph-based AI/ML solutions, and graph database architecture (with an emphasis on Neo4j) in support of our data and AI strategy execution.
The ideal candidate brings deep expertise in graph modeling and implementation, ontology development, graph machine learning, and semantic technologies, and is skilled in understanding business goals and requirements and reflecting them in systems implementations that consider current and emerging needs. You will collaborate across data science, engineering, and product teams to embed graph intelligence into enterprise systems using platforms like Neo4j and Databricks.
Lead the enterprise knowledge graph development and operationalization, including data modeling, ontology and taxonomy development, semantic modeling, and integration with machine learning and business platforms.
Design and manage complex graph data models and ontologies using W3C standards (RDF, OWL, SKOS, SHACL) to support data standardization, discovery, and analytics.
Develop and implement graph-based machine learning models (e.g., Drive the use of NEO4J for graph data storage, querying (Cypher), and integration into enterprise pipelines.
Collaborate with AI/ML engineers to fine-tune LLMs and integrate graph data into intelligent agents and semantic search systems.
Champion the adoption of graph-based AI/ML, especially in online higher education use cases.
Stay abreast of developments in graph database, graph AI/ML, semantic web, agent-based systems, and enterprise AI platforms.
Master's Degree in Information science, Library and Information Science, Data Science, Ontology, Computer Science, Engineering or a related field.

5+ years of hands-on experience designing and implementing knowledge graphs using NEO4J, including Cypher queries and graph modeling, and graph database design and operations best practices.

• Proven experience implementing graph-based machine learning models (e.g., Experience working with Databricks and Spark-based data workflows.
• Demonstrated ability to lead enterprise-level data integration initiatives and semantic modeling projects.
• Strong programming skills in Python, including ML libraries (e.g., DGL, NetworkX, NEO4J Python driver).
• Experience supporting online platforms, ideally in online education or digital business ecosystems.

Degree in Information science, Library and Information Science, Data Science, Ontology, Computer Science, Engineering or a related field.

Experience integrating knowledge graphs with LLMs, prompt engineering, and AI agents (e.g., Familiarity with graph query optimization, entity resolution, and knowledge extraction from structured and unstructured data.
Experience with graph data cataloging tools (e.g.,