Senior Consultant Semantic Data & AI Engineer

• Design and build knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products; translate business concepts into machine-readable semantic models
• Develop end-to-end data pipelines for acquiring, transforming, mapping, validating, and loading information; implement data-quality controls using SHACL validation
• Integrate knowledge graphs with generative AI, RAG/GraphRAG, semantic search, and LLM applications; support NLP and document-intelligence use cases
• Develop Python or Java based data transformations, APIs, and services; create automated tests and support CI/CD pipelines and production deployments
• Lead technical workstreams, mentor junior consultants, and facilitate requirements and modeling sessions with stakeholders
• Participate in graph-platform evaluations and production deployments; produce technical designs, semantic models, and comprehensive documentation
• Build vector search and semantic search capabilities; demonstrate proficiency in cloud platforms and containerized deployments

Our client is seeking a Senior Consultant Semantic Data & AI Engineer with 8 12 years of experience to design and deploy knowledge graphs, semantic layers, and AI-driven data solutions. This role combines deep expertise in graph technologies and semantic standards with practical application of modern machine learning and cloud platforms., * 8 12 years of professional experience in data engineering, semantic technologies, or related fields

• Expert-level knowledge of semantic standards and languages: RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, and Turtle
• Hands-on experience with graph databases and platforms: Neo4j, Stardog, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, or TypeDB
• Strong programming skills in Python and Java; proficiency with Git, CI/CD, automated testing, and containerization
• Demonstrated expertise in data pipelines, NLP, machine learning, and vector search technologies
• Experience with cloud platforms: AWS, Azure, Google Cloud, or tools such as Databricks, Snowflake, BigQuery, Redshift, or Microsoft Fabric
• Agile methodology experience and a proven track record of delivering technical solutions in collaborative environments