Semantic AI Engineer

AbbVie•North Chicago, IL

5h•$78,500 - $141,000

About The Position

AbbVie’s global Information Research (IR) group has a mission to unlock information that makes cures possible. Within IR, the Enterprise Knowledge Accelerator (EKA) team serves as a trusted knowledge partner for clients in R&D and the Corporate Business & Strategy Office (CBSO), helping drive innovation, knowledge sharing, and faster decisions that support advancement of AbbVie’s pipeline. EKA is a global organization with presence in Lake County, Illinois, Boston, Massachusetts, and Ludwigshafen, Germany. Within EKA, the Reference Data Architecture (RDA) team is building Ontoverse to develop AbbVie’s enterprise semantic capabilities by combining GenAI technologies, reference data expertise, and semantic architecture. RDA creates the semantic layer that connects high-quality internal and external ontologies, controlled vocabularies, and reference standards with major company data initiatives and platforms, making knowledge more connected, computable, and actionable across the enterprise. The Semantic AI Engineer will build and operationalize software capabilities that expose these semantic assets through Enterprise Ontology Services (EOS) for use in platforms such as Enterprise Product Master Data (EPMD), Dataverse, and controlled technology development frameworks like SHIFT. The role applies software engineering and semantic knowledge representation to create reusable components, APIs, MCP tools, agents, and AI-enabled services that support discovery, inference, harmonization, data integration, and decision-making at scale, while contributing to CI/CD practices that enable reliable delivery and ongoing operational support. Working closely with platform, product, ontology, data, and governance teams, the role will also help deliver implementation solutions that embed FAIR data principles into GenAI-generated software assets from the start.

Requirements

Bachelor’s Degree in Data Science, Computer Science, Informatics, Software Engineering, Semantic Technologies or any related field and 5 years of experience; or Master’s Degree and 4 years of experience.
Demonstrated experience building production-quality data, software, AI, or semantic technology solutions, including APIs, MCP tools, agents, services, integrations, or reusable platform components, common technologies, and formats (e.g., Rest APIs, XML, JSON, Python libraries such as Pydantic).
Working knowledge of ontologies, controlled vocabularies, knowledge graphs, semantic standards (OWL, RDF, SPARQL), metadata, mapping, normalization, and FAIR data principles.
Ability to translate business and governance requirements into scalable technical designs that make semantic assets accessible to applications, AI agents, search, and data integration workflows.
Demonstrated ability to learn and apply emerging technologies, operate within timelines, and produce clear technical documentation for enterprise adoption, contributing to CI/CD practices that enable reliable delivery and ongoing operational support.
Strong collaboration, stakeholder management, and communication skills, with the ability to work across platforms, governance, ontology, and product teams.
Comfortable working in a fast paced, highly collaborative, dynamic work environment with constantly shifting priorities.
Demonstrate an interest in working cross-functionally and in inter-disciplinary teams with an ability to effectively communicate, both verbally and in writing, with scientists and non-scientists.
Innate scientific curiosity, technical creativity, and innovative thinking. Motivated to break new ground in the field of information analysis and insights generation.
Fluency in English

Responsibilities

Design, build, and operationalize AI-driven semantic solutions that embed enterprise ontologies and semantic assets into Enterprise Product Master Data initiative, the Dataverse, and related enterprise platforms through EOS.
Engineer and translate ontologies, controlled vocabularies, mappings, semantic contracts, and reference standards into machine-consumable services, APIs, agent tools, and reusable software components.
Enable semantic knowledge structures to actively drive inference, search, normalization, query expansion, entity resolution, and data integration across enterprise-scale workflows.
Partner with the Standards & Governance Expert to define implementation patterns, decision processes, and quality gates that embed FAIR data principles into SHIFT-generated software assets from project initiation.
Collaborate with platform, product, data, ontology, and governance teams to align semantic services with business requirements, enterprise architecture, and scalable delivery practices.
Develop and maintain technical documentation, integration patterns, reusable examples, and guidance that help teams consume EOS capabilities consistently and effectively.
Understand and adhere to applicable corporate standards, including code of conduct, data security, GxP compliance where relevant, software development lifecycle expectations, and responsible AI practices.
Monitor and be attuned to new technology trends relevant for knowledge analysis and insights discovery.
Achieve great results, while demonstrating key AbbVie values and behaviors.