Semantic AI/ML Architect

Overview

In this role you will design and maintain semantic data frameworks to standardize enterprise data. You will build ontologies and knowledge graphs, enforce data quality through semantic rules, and collaborate with AI teams to embed semantic structures in intelligent applications. The position is industry-agnostic, emphasizing strong semantic web expertise and enterprise applicability. You will work with cross-functional teams to scale semantic models and support AI-driven solutions with context-rich data.

Responsibilities

• Design, develop and maintain ontologies (OWL/RDF or similar) to model enterprise data domains and relationships
• Build and manage enterprise knowledge graphs, integrating diverse data sources into a unified graph model
• Create and optimize SPARQL queries and endpoints for advanced search and analytics
• Define and enforce semantic validation rules (SHACL/OWL constraints) to ensure data quality and interoperability
• Collaborate with software engineers, data architects and IT to embed semantic models into data pipelines, APIs and databases
• Partner with AI/ML teams to integrate knowledge graphs into AI-driven solutions and support reasoning over ontologies
• Promote and codify semantic standards and best practices across the organization
• Stay current with semantic web standards and contribute to internal guidelines for semantic data management

Key requirements

• Ontology design & maintenance experience (OWL/RDF)
• Semantic web proficiency (OWL, RDF, SPARQL)
• Knowledge graph development/maintenance in an enterprise setting
• Data modelling, architecture and integration of heterogeneous data sources
• Programming/scripting ability (Python, Java or similar)

• Strong collaboration and cross-functional communication
• Ability to explain complex semantic concepts to non-technical stakeholders
• Proactive problem solving and documentation
• OWL
• RDF
• SPARQL

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