Senior Applied AI Engineer/Scientist – Semantic AI, Central Reliability Maintenance Engineering
Core
Lead semantic layer and knowledge intelligence initiatives for agentic and non-agentic AI, focusing on ontology design, knowledge graphs, and explainability for Amazon's Central Reliability Maintenance Engineering.
Role type
Senior Applied AI Engineer/Scientist (Knowledge Engineering & Semantic AI)
Builds
Production-grade knowledge graphs, graph-based AI solutions, and semantic foundations for autonomous workflows and data discovery.
Domain
Logistics & Supply Chain (Warehouse Operations) + Knowledge Engineering
Deliverable
production ML models | product features
Required skills
Knowledge graph development, semantic modeling (RDF, OWL), querying languages (SPARQL, Gremlin, Cypher), LLM integration, MLOps, ontology design, causal reasoning, entity extraction, model optimization
Preferred skills
AWS services expertise, graph theory application, graph visualization, clean modular ML code design
Technologies
Knowledge graphs, LLMs, vector databases, GPUs/Neuron/TPU, SPARQL, Gremlin, Cypher, RDF, OWL
Responsibilities
Develop ontological foundations for autonomous workflows; design and deploy graph-based AI solutions combining KGs and LLMs; define knowledge pipelines for unstructured data enrichment; operate graph and vector databases; optimize inference pipelines for production constraints; establish best practices for knowledge engineering; mentor colleagues on semantic modeling.
Seniority
Senior, hands-on IC with mentorship
