AI Knowledge Engineer

AI Knowledge Engineer at Proofpoint focused on enabling AI systems to operate across distributed enterprise knowledge ecosystems by creating semantic representations, governance frameworks, and knowledge architectures that unify information while preserving ownership, lineage, and trust. Responsibilities include designing and maintaining semantic models, building knowledge representations, developing and enhancing knowledge graphs, creating and maintaining taxonomies/ontologies/metadata standards, and designing ingestion/extraction workflows. Collaborates with AI and ML teams to integrate knowledge systems with LLM-powered applications, retrieval systems, and agentic workflows; develops evaluation frameworks for AI agents and knowledge-driven systems; and advances federated knowledge initiatives while upholding ownership and compliance boundaries. The role requires a solid foundation in semantic modeling, knowledge representation, data governance, and LLM technologies, with a mid-to-entry level pedigree and a strong aptitude for solving complex information-management challenges. The candidate should be comfortable contributing to governance standards, enabling AI-ready knowledge assets, and communicating with stakeholders to address information challenges and drive business impact.