Data / Ontology Engineer - Agentic AI Platform

This is a position suitable for passionate professionals who want to work for a leading European Insurance Group on a very flexible work schedule.

You will work as part of a multinational group with true, large, enterprise-wide systems, complex architectures and real life constraints (speed, performance, non-stop systems availability) and are going to be part of an agile team aimed at designing and implementing enterprise level solutions.

• Contract duration : permanent
• Schedule : full-time (8 hrs/day, Monday to Friday)

Your responsibilities

• Implement and maintain domain ontologies, taxonomies, knowledge graph structures, and semantic assets defined for the Agentic AI Platform.
• Translate business concepts and relationships into machine-readable models and validation rules.
• Build data and embedding pipelines that transform source content into governed vector and graph representations.
• Implement and operate knowledge graph entities, mappings, queries, validation, versioning, and publishing processes.
• Manage vector stores and support hybrid retrieval, grounding, and RAG data quality improvements.
• Model country-specific document types and local taxonomies while aligning them with reusable group concepts.
• Automate quality checks, lineage, metadata capture, and regression testing for ontology and knowledge assets.
• Collaborate with the Data Architect, domain experts, AI Engineers, Integration Engineers, and country teams.

Required skills

• Several years of experience in data engineering, ontology engineering, knowledge graph engineering, semantic technologies, or related fields.
• Hands-on experience with RDF, OWL, SKOS, SHACL, SPARQL, graph modelling, or comparable semantic standards and tools.
• Practical knowledge of graph databases such as Neo4j and of data mapping, entity resolution, metadata, and validation techniques.
• Strong Python skills and experience building ETL/ELT, document processing, or knowledge ingestion pipelines.
• Experience with embeddings, vector databases, hybrid retrieval, RAG pipelines, and retrieval quality evaluation.
• Knowledge of version control, automated testing, CI/CD, data quality, and reproducible engineering practices.
• Ability to work with business subject-matter experts and convert domain language into precise technical models.
• Good analytical, documentation, collaboration, and English communication skills; insurance knowledge is an advantage.

Compensation & benefits

• Very stable work environment, as part of a large Insurance Multinational Group
• Flexible work program, respecting your own private time
• Attractive remuneration package
• Lunch tickets
• Special Days vouchers (Women’s Day, Children's Day, Christmas, Easter)
• Private pension and private health insurance contribution
• Time off when holidays fall on a weekend (up to 3 days/year)
• Exchange of experience and training with international professionals, as a premise for personal development
• Team building events.