Senior Semantic Engineer

Senior Semantic Engineer to design and implement semantic data frameworks that provide a shared structure for enterprise data. You will focus on building and maintaining ontologies and knowledge graphs, enforcing data quality through semantic validation rules, and collaborating with AI teams to integrate semantic structures into intelligent applications. The role is industry-agnostic and requires strong expertise in semantic web technologies.

What You'll Do

• Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar) that model key enterprise data domains, collaborating with domain experts to capture concepts and validate that the ontology accurately represents business knowledge.
• Knowledge Graph Development: Build and manage enterprise knowledge graphs based on defined ontologies, linking diverse data sources into a unified graph data model; configure graph databases or triple stores, populate RDF triples, and optimize it for query performance and scalability.
• Semantic Querying (SPARQL): Create and optimize SPARQL queries to enable efficient retrieval, integration, and analysis of data from the knowledge graph; develop semantic queries and endpoints for advanced search and analytics.
• Validation Rules & Data Quality: Implement semantic validation rules and consistency checks (e.g., SHACL or OWL constraints) to ensure data integrity; define data modelling conventions and business rules to keep enterprise data interoperable across systems.
• Integration with Enterprise Systems: Collaborate with software engineers, data architects, and IT teams to embed the ontology and knowledge graph into the organization's data infrastructure and workflows; embed semantic models in data pipelines, APIs, and databases.
• Collaboration & Cross-Functional Support: Partner with AI/ML teams to incorporate the knowledge graph into AI-driven solutions, and team up with business analysts or data stewards to align the semantic models with business needs; communicate semantic concepts to non-technical stakeholders and provide training/documentation.
• Integration with AI Agents: Work with AI agents and LLM teams to leverage the ontology and knowledge graph for intelligent applications; enable AI chatbots to use the knowledge graph for context-aware responses and support reasoning over ontologies.
• Standards & Best Practices: Stay current with emerging semantic web standards, tools, and best practices; continuously improve the semantic architecture by adopting relevant metadata standards and establishing internal guidelines for semantic data management.

What We're Looking For

• Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar).
• Semantic Web Proficiency: Strong knowledge of semantic web technologies and standards, including OWL, RDF, and SPARQL.
• Knowledge Graph Experience: Practical experience building or maintaining knowledge graphs in an enterprise setting.
• Data Modelling & Integration Skills: Understanding of data modelling, data architecture, and integrating heterogeneous data sources; ability to map relational or NoSQL data to an ontology.
• Programming Skills: Proficiency in Python, Java, or similar.

Nice to Have

• Metadata Standards: Familiarity with Dublin Core, schema.org, or other vocabularies.
• Experience applying these standards to annotate or integrate data.
• AI and LLM Integration: Experience working on AI/LLM projects where ontologies or knowledge graphs enhanced performance.
• Enterprise System Integration: Proven experience integrating semantic technologies into existing enterprise systems.
• Tools & Platforms: Hands-on experience with ontology and knowledge graph tools.

Compensation & Benefits

• Salary and benefits not specified in the posting.