AI Ontology
The AI Ontology role involves designing and maintaining enterprise ontologies, taxonomies, and semantic models within the financial services sector. This position supports the development of knowledge graphs, decision structures, and rule systems to enable enterprise-wide AI pipelines. The role is integral to advancing data analysis, data modelling, and AI engineering initiatives.
About the Company
The organisation is engaged in delivering data and analytics solutions to top-tier financial services clients. It fosters a growing team of data practitioners focused on innovative data programmes and AI-driven insights.
Role Overview
The Senior Data Consultant will support and lead ontology development and semantic modelling efforts. Working closely with Data, Architecture, and AI teams, the role involves creating reusable semantic frameworks across multiple business domains. Success depends on translating business knowledge into machine-readable models and embedding knowledge graph capabilities into AI products and domain agents.
Key Skills & Experience
- Lead the design and development of enterprise ontologies, taxonomies, and semantic models for financial services.
- Build and manage enterprise knowledge graphs to support natural language access and reasoning.
- Define business entities, relationships, rules, and vocabularies using semantic standards (RDF, OWL, SKOS).
- Translate business policies and regulatory requirements into semantic models.
- Partner with cross-functional teams to embed ontology and knowledge graph capabilities into AI products.
- Establish scalable semantic frameworks applicable across multiple domains.
- Proven experience in ontology modelling, knowledge engineering, or semantic data architecture.
- Experience building enterprise knowledge graphs and designing ontologies.
- Strong understanding of taxonomy design, semantic modelling, controlled vocabularies, and ontology management.
- Conceptual and logical data modelling skills for complex business domains.
- Knowledge of how ontologies and knowledge graphs support LLMs, semantic search, and reasoning.
- Experience with structured rule definitions and metadata standards (YAML, JSON).
- Excellent stakeholder engagement skills, including facilitating domain modelling workshops.
Nice to Have
- None specified.
Key Responsibilities
- Design and maintain enterprise ontologies, taxonomies, and semantic models across financial services.
- Develop and manage enterprise knowledge graphs to enable natural language reasoning and AI insights.
- Define business entities, relationships, rules, and vocabularies using semantic standards.
- Translate business policies and regulatory requirements into machine-readable semantic models.
- Collaborate with Data, Architecture, and AI teams to integrate ontology and knowledge graph capabilities.
- Establish scalable semantic frameworks for reuse across various business domains.
Requirements
- Proven experience in ontology modelling, knowledge engineering, or semantic data architecture.
- Experience building enterprise knowledge graphs and designing ontologies is mandatory.
- Strong enterprise data modelling experience with knowledge graph and ontology/taxonomy expertise.
- Strong understanding of taxonomy design, semantic modelling, controlled vocabularies, and ontology management.
- Demonstrated ability to model complex business domains and relationships.
- Experience supporting LLMs, semantic search, and reasoning capabilities.
- Knowledge of structured rule definitions and metadata standards (YAML, JSON).
- Right to work in the relevant region.
- Location: On-site in Asia.
- Employment type: Permanent.
- Job duration: 2 weeks.
- Start date: 18/08/2026.
- Work environment: Onsite.
If you have the relevant skills and experience, please apply with an updated CV.
