Role = Ontology Consultant

Duration = Initial 6-month contract

Location = UK (Remote)

Job Spec

Key Responsibilities

1. 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.

1. 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.

1. 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

Required Skills and Qualifications

• 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.