telus-digital - Staff AI Engineer (Data Ontologist)

• Strong experience in designing semantic systems, ontologies, or knowledge graphs within complex data environments. • Hands-on experience with knowledge representation techniques, including taxonomy design, entity-relationship modeling, and graph-based structures. • Experience working with LLM-based systems, particularly in context engineering, retrieval-augmented generation (RAG), or agentic AI architectures. • Deep understanding of embeddings, vector databases, and retrieval strategies, and how they interact with structured semantic layers. • Experience designing context pipelines that integrate multiple data sources (APIs, databases, documents) into coherent inputs for AI systems. • Familiarity with frameworks and tools related to graph databases (e.g., Neo4j), semantic layers, or metadata management. • Strong understanding of trade-offs in context construction, including latency vs. completeness, precision vs. recall, and static vs. dynamic context. • Experience working in cloud environments (AWS, Azure, GCP) and integrating AI systems into production-grade architectures. • Ability to communicate complex semantic and AI concepts clearly across technical and business stakeholders. • Experience with context graphs and advanced context orchestration patterns for agentic systems. • Background in information science, knowledge engineering, or ontology design. • Experience aligning AI systems with enterprise knowledge bases (e.g., CMS, knowledge management systems). • Familiarity with evaluation frameworks for context quality and downstream agent performance. • Experience designing reusable, cross-domain semantic layers for large organizations.