Luxoft
Senior Semantic Engineer – Knowledge Graphs, Ontologies & AI Integration

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Senior Semantic Engineer
We're looking for an experienced Senior Semantic Engineer to help shape the future of enterprise knowledge management through semantic technologies, ontologies, and knowledge graphs. This is an exciting opportunity for a specialist who is passionate about creating structured, interconnected data ecosystems that power intelligent applications, AI solutions, and enterprise-wide data understanding. As a Senior Semantic Engineer, you will design and maintain enterprise ontologies and knowledge graphs that provide a shared understanding of data across the organisation. Working closely with Data, AI, Engineering, and Business teams, you'll help transform disconnected data into meaningful, connected knowledge that drives innovation, improves decision-making, and enhances AI capabilities.
What You'll Be Doing
- Design, develop, and maintain enterprise ontologies using OWL, RDF, and related semantic technologies
- Collaborate with business and domain experts to model real-world concepts, entities, and relationships
- Build and manage enterprise knowledge graphs that connect and enrich data from multiple sources
- Configure, maintain, and optimise graph databases and triple stores for performance and scalability
- Develop and optimise SPARQL queries to support analytics, search, and knowledge discovery
- Define and enforce semantic validation rules using technologies such as SHACL and OWL constraints
- Establish standards for data quality, consistency, interoperability, and governance
- Integrate semantic models into enterprise systems, APIs, applications, and data platforms
- Work alongside Data Architects and Engineers to embed semantic capabilities into enterprise workflows
- Partner with AI and Machine Learning teams to enhance LLM and AI-driven solutions with semantic context
- Support the use of knowledge graphs for intelligent agents, reasoning engines, contextual search, and retrieval
- Produce documentation, training materials, and best practice guidance to drive adoption across the organisation
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Skills & Experience
Semantic Technologies
- Strong expertise in Semantic Web technologies and standards
- Deep knowledge of OWL (Web Ontology Language)
- Strong experience with RDF (Resource Description Framework)
- Advanced SPARQL development and query optimisation skills
- Experience implementing semantic validation frameworks and data quality controls
Ontology Engineering
- Proven experience designing, developing, and maintaining complex ontologies
- Ability to translate business concepts into scalable semantic models
- Experience creating shared vocabularies and data standards across enterprise domains
- Strong understanding of ontology governance and lifecycle management
Knowledge Graphs
- Hands-on experience building and maintaining enterprise knowledge graphs
- Experience linking and integrating data from diverse sources
- Familiarity with graph databases, triple stores, and linked data platforms
- Understanding of graph modelling principles and enterprise-scale semantic architectures
Data Architecture & Integration
- Strong knowledge of data modelling and enterprise data architecture
- Experience integrating heterogeneous data sources into unified semantic frameworks
- Ability to map relational and NoSQL data structures into ontology-based models
- Experience integrating semantic technologies into enterprise applications and platforms


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Programming & Development
- Proficiency in Python, Java, or similar programming languages
- Experience developing integrations, automation, and semantic processing applications
- Understanding of APIs, data pipelines, and software development best practices
Nice to Have
- Experience working with metadata standards such as Dublin Core, schema.org, SKOS, or industry-specific ontologies
- Experience integrating ontologies and knowledge graphs with AI, LLMs, and intelligent agents
- Knowledge of semantic search, reasoning engines, and retrieval systems
- Experience integrating semantic solutions into large-scale enterprise platforms
- Familiarity with leading ontology management and knowledge graph toolsets
- Exposure to AI-driven knowledge retrieval, disambiguation, and context-enrichment solutions
Why Join?
This role sits at the intersection of Data, Knowledge Management, and Artificial Intelligence. You'll have the opportunity to build foundational semantic capabilities that enable smarter data, more effective AI systems, and greater enterprise understanding across the organisation.
If you're passionate about Knowledge Graphs, Ontologies, Semantic Web technologies, and the future of AI-powered knowledge systems, we'd love to hear from you.
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