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Ontology Data Engineer

Type:Contract
Location:Remote
Category:Data (Analysis, Science, Architecture)
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Ontology Data Engineer

  • Contract Role, Remote

RedStream Technology is searching for a Data engineer with professional ontology experience. 

Key Responsibilities

  • Ontology Development and Knowledge Engineering
  • Design, build, and maintain ontologies to support data integration and semantic reasoning.
  • Leverage ontologies to enhance data pipelines and enable advanced knowledge engineering solutions.
  • Collaborate with AI teams to ensure ontology structures efficiently support Agentic AI applications, including RAG pipelines and Agent Orchestration.

Graph Database Expertise

  • Work with both Semantic Graph and Property Graph technologies, understanding their unique architectures and use cases.
  • Utilize Semantic Graph tools for rule-based inference and semantic reasoning.
  • Employ Property Graph tools like Neo4j, Amazon Neptune, and TigerGraph for network analytics and data exploration.
  • Integrate graph solutions with AI and machine learning systems, ensuring seamless knowledge retrieval and reasoning.

Network Science Application

  • Apply network science techniques to analyze and interpret complex relationships within graph data.
  • Develop algorithms and models to extract insights from graph structures and relationships.
  • Use network insights to enhance AI systems’ ability to reason across interconnected data sets.

Skills: 

  • Strong expertise in ontologies, including their design, implementation, and application in real-world scenarios.
  • Proficiency in graph database technologies, with hands-on experience in both Semantic Graph and Property Graph systems.
  • Solid understanding of network science concepts and their practical applications in graph engineering.
  • Familiarity with standards such as RDF and W3C for Semantic Graphs, as well as bespoke standards for Property Graphs.
  • Ability to mentor and train junior team members, fostering a culture of learning and growth.
  • Experience integrating AI considerations (like LLM-based retrieval, RAG pipelines, and Agent Orchestration) into graph ecosystem design.

Preferred Qualifications

  • Experience with data pipelines and integrating graph databases into larger data ecosystems.
  • Knowledge of rule-based inference systems and network analytics tools.
  • Strong problem-solving skills and the ability to work independently on complex technical challenges.
  • Prior exposure to enterprise AI initiatives, demonstrating an understanding of how knowledge graphs support agent-based architectures.

Education:      

Minimum Master's degree ideally in engineering, science or another technical or business related field