Knowledge Engineering Consultant (all genders)
Kronberg, Campus Kronberg 1
Posted 1d ago
Job Location
Kronberg, Campus Kronberg 1
Tech Stack
Remote Work Policy
On-site
Categories
AI Engineer
About the job
This role is for a strong individual contributor knowledge engineer who is growing into a team lead. You will be well-versed in the full knowledge graph development lifecycle, formulating real-world problems into practical, efficient, and scalable AI and Knowledge Graph solutions. You will work hands-on across the lifecycle from ingestion through modeling, curation, and deployment, applying current methodologies and techniques. You will also begin to guide junior engineers and stay current with knowledge engineering, generative AI, LLM, and multi-modal models, looking for opportunities to apply them. Collaboration with users, use case representatives, engineers, architects, and UI designers is key to delivering end-to-end solutions.
Responsibilities
- Build Knowledge Graph components to transform a client's data architecture.
- Design, develop, and implement AI and semantic solutions, ensuring clean integration with the broader system.
- Work alongside project teams and delivery leads.
- Build strong working relationships with client counterparts.
- Help assemble supporting evidence for recommended semantic layer solutions.
- Support sales efforts when called upon.
- Continuously develop skills in cutting-edge Data & AI solutions, especially agentic technologies, and share knowledge with the team.
Requirements
- Bachelor's degree or equivalent.
- At least 3 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL).
- Experience in schema design, ontology management, and KG curation.
- Experience designing and developing KG solutions and graph-based ML models.
- Proven experience with end-to-end data pipeline implementation for AI applications (especially LLMs), with hands-on design and configuration.
- Strong knowledge and working experience with relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases.
Benefits
- Hybrid working and flexible working models.
- Access to certifications, learning platforms, and over 30,000 training opportunities.
- Employee Share Purchase Program (ESPP) with preferential conditions.
- Employee Assistance Program (EAP) and wellbeing resources.
- Opportunity to work on cutting-edge Knowledge Graph, Generative AI, and agentic AI projects.