Luxoft
Semantic AI/ML Architect
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Working model: fully remote from the UK.
Employment
Official full-time employment through a Luxoft Legal Entity.
Why Luxoft?
We offer a comprehensive benefits package to support your health, wellbeing, and financial security:
- Private medical & dental insurance (BUPA)
- Life insurance (3x salary) & income protection
- 25 days annual leave + 8 public holidays + paid sick leave
- Pension scheme (AEGON UK)
- Interest-free company loan
About the Role
We are seeking a Senior Semantic Engineer to design and implement semantic data frameworks that provide a shared structure for enterprise data.
In this role you will focus on building and maintaining ontologies and knowledge graphs, enforcing semantic validation rules for data quality, and collaborating with AI teams to integrate these semantic structures into intelligent applications.
The position is industry-agnostic, emphasizing strong semantic web expertise and the ability to apply it in any enterprise context.
Responsibilities
- Design & Maintain Ontologies Develop and manage enterprise ontologies using technologies such as OWL and RDF. Work closely with business and domain experts to model real-world concepts, define relationships between data, and create a common language across the organization.
- Build Enterprise Knowledge Graphs Create and maintain scalable knowledge graphs that connect data from multiple sources into a unified, searchable structure. Configure graph databases, load semantic data, and ensure high performance and reliability.
- Develop Semantic Queries (SPARQL) Write and optimize SPARQL queries to enable efficient data discovery, integration, and analytics. Support advanced search capabilities and help teams extract valuable insights from connected data.
- Ensure Data Quality & Governance Define and implement validation rules using standards such as SHACL and OWL. Ensure data consistency, integrity, and compliance with established modelling standards and business rules.
- Integrate Semantic Technologies with Enterprise Systems Partner with software engineers, architects, and data teams to embed ontologies and knowledge graphs into data pipelines, APIs, applications, and enterprise platforms.
- Collaborate Across Teams Work with business stakeholders, data stewards, AI/ML engineers, and technical teams to align semantic models with business needs. Promote adoption of semantic technologies through documentation, training, and knowledge sharing.
- Enable AI & Intelligent Applications Support the integration of knowledge graphs and ontologies with AI solutions, including LLM-powered applications and AI agents. Help improve contextual understanding, knowledge retrieval, reasoning capabilities, and overall AI performance.
- Drive Best Practices & Innovation Stay up to date with emerging semantic web technologies, industry standards, and best practices. Contribute to the evolution of the organization's semantic architecture and establish guidelines for effective knowledge management.
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Skills
- Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar).
- Semantic Web Proficiency: Strong knowledge of semantic web technologies and standards - specifically, hands-on proficiency with OWL (Web Ontology Language) and RDF (Resource Description Framework) for ontology modelling, as well as SPARQL for querying graph data.
- Knowledge Graph Experience: Practical experience building or maintaining knowledge graphs or linked data systems in an enterprise setting.
- Data Modelling & Integration Skills: A solid understanding of data modelling principles, data architecture, and integrating heterogeneous data sources. You should be capable of abstracting real-world entities into a semantic schema and mapping relational or NoSQL data to an ontology.
- Programming Skills: Proficiency in at least one programming or scripting language (such as Python, Java, or similar)
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Nice-to-Have Skills
- Metadata Standards: Familiarity with metadata standards and vocabularies such as Dublin Core, schema.org, or other industry-specific ontologies/taxonomies. Experience applying these standards to annotate or integrate data
- AI and LLM Integration: Experience working on projects that involve AI agents or large language models, where ontologies or knowledge graphs were used to improve AI performance.
- Enterprise System Integration: Proven experience integrating semantic technologies into existing enterprise systems or data platforms.
- Tools & Platforms: Hands-on experience with ontology and knowledge graph tools is beneficial.
Languages
- English: C1 Advanced
Luxoft is committed to fostering a diverse and inclusive workplace. We show fairness to all throughout our talent acquisition and management process.
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