Ontology & Semantic Modeler, Data Context Layer

About the role

- Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. - Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. - Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats. Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company's IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy. A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers. Role Overview This role is part of a broader enterprise initiative to establish a Data Context Layer (DCL) - a foundational capability designed to provide consistent, reusable, and scalable context across enterprise data products. The DCL is intended to address challenges related to data fragmentation, lack of shared semantics, and inconsistent interpretation of data across systems and products . It establishes a unified layer for representing context, relationships, and meaning, enabling downstream products to operate with greater consistency, interoperability, and intelligence. In addition, the DCL plays a critical role in enabling agentic AI capabilities across the enterprise by providing the structured context and semantic grounding required for intelligent agents to operate reliably. This includes ensuring that agent-driven workflows and decisions are based on consistent, governed, and interpretable data context , reducing risks associated with fragmentation, ambiguity, and lack of control. Within this initiative, we are seeking an Ontology and Semantic Modeler to design, develop, and maintain the semantic foundations of an enterprise platform that enables teams to publish, discover, and consume standardized data context through self-service . This role is responsible for creating and governing ontologies, semantic models, and related standards that make enterprise context consistent, reusable, and machine-readable across systems and AI-enabled workflows. The ideal candidate has strong experience in ontology engineering, semantic modeling, OWL/RDF, knowledge representation, and metadata-driven design . Familiarity with agentic AI, prompt engineering, and context engineering is required, as the semantic layer will support both human users and AI/agentic consumers of context.

Responsibilities

• Design and maintain enterprise ontologies and semantic models that represent key business concepts, entities, relationships, and rules.
• Define modeling standards, conventions, and lifecycle practices for semantic assets across the enterprise.
• Collaborate with product, architecture, engineering, governance, and domain experts to translate business needs into formal semantic structures.
• Ensure semantic models support standardized, self-service serving of data context.
• Develop and maintain OWL/RDF-based models, vocabularies, taxonomies, and controlled terminologies as needed.
• Support mapping and alignment between source systems, canonical models, and context-serving interfaces.
• Help define validation rules, versioning strategies, and governance processes for semantic assets.
• Ensure ontologies are production-ready, reusable, and aligned to platform requirements for discoverability, access, and interoperability.
• Partner with technical teams to support integration with semantic layers, knowledge graphs, MCP, A2A, Protégé and timbr-like technologies where relevant.
• Contribute to the design of context structures that improve AI and agentic system grounding, prompt quality, and context delivery.
• Support testing, documentation, and quality assurance of semantic models before release into production.
• Work with stakeholders to resolve modeling ambiguities and establish shared understanding of enterprise concepts.
• Required Qualifications
• 5+ years of experience in ontology modeling, semantic modeling, information modeling, or knowledge representation.
• Strong knowledge of

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