Senior Knowledge Graph Engineer & Semantic Architect, Central Reliability Maintenance Engineering

Amazon's Central Reliability Maintenance Engineering (C-RME) team is seeking a Senior Knowledge Graph Engineer & Semantic Architect to spearhead their next-generation information architecture initiatives. This role sits at the intersection of semantic technologies, AI, and enterprise data architecture, working to revolutionize how Amazon handles complex data relationships and knowledge representation.

The position involves leading the development of sophisticated knowledge graph solutions that will power Amazon's maintenance and reliability operations through 2025-2027 and beyond. You'll be working with cutting-edge technologies, including AI text extraction and Large Language Models (LLMs), while designing scalable knowledge pipelines that ensure reliable information architecture across the organization.

As part of the Decision Science & Technology (DST) team within RME, you'll contribute to a broader mission of using science and data to drive scalable maintenance practices across Amazon's global operations. The team maintains and optimizes technologies ranging from large, modern warehouses with robotics to small, high-speed facilities positioned close to customers.

Key responsibilities include architecting knowledge graph solutions, developing ontologies, implementing semantic layers, and establishing best practices for knowledge engineering processes. You'll work closely with business stakeholders to translate requirements into graph-based solutions while ensuring high performance and reliability.

The ideal candidate brings deep expertise in semantic technologies, graph databases, and enterprise architecture, combined with strong communication skills to bridge technical and business perspectives. This role offers the opportunity to shape how one of the world's most innovative companies leverages knowledge graphs and semantic technologies to drive operational excellence.

Working at Amazon means joining a culture of innovation where every day is treated as Day One. You'll be part of a team that uses machine learning and advanced analytics to develop predictive models for maintenance, spare parts, energy consumption, and more, all while supporting Amazon's Climate Pledge commitments.