Semantic AI Engineer

Role: Semantic AI Engineer focused on building and operationalizing AI-driven semantic solutions within AbbVie's enterprise knowledge platform. Responsibilities: design and implement semantic assets such as ontologies, vocabularies, mappings, and semantic services for enterprise data initiatives like EPMD and Dataverse; develop APIs, agents, and reusable components to enable inference, search, data normalization, and integration; collaborate across platform, data, governance, and ontology teams to embed FAIR data principles; produce technical documentation and ensure compliance with standards including GxP and responsible AI. Requirements: Bachelor's in Data Science, Computer Science, or related field with 5+ years (or Master's with 4+ years) experience; proven experience in building semantic, AI, or data solutions, including APIs, MCP tools, or knowledge graphs; strong knowledge of ontologies, RDF, OWL, SPARQL, and FAIR data principles; ability to translate governance and business needs into scalable technical solutions; excellent collaboration and communication skills. Preferred: familiarity with GenAI technologies, semantic standards, and enterprise data integration. High-Value: focus on semantic architecture supporting discovery and inference at scale within biopharma data ecosystems; contributes to enterprise knowledge connectivity, enabling advanced insights and decision-making in R&D. Work setup: not specified, but operates within a fast-paced, collaborative environment.