Roles & Responsibilities:

- Design, develop, and maintain enterprise ontologies and semantic knowledge models to organize business information in a structured and scalable manner.
- Build and manage knowledge graphs by connecting data across multiple enterprise systems to ensure consistency, accuracy, and interoperability.
- Model relationships between products, customers, services, and business entities to enhance enterprise search, analytics, and AI-powered applications.
- Collaborate with business stakeholders to gather requirements and translate them into semantic data models and ontology frameworks.
- Develop and maintain ontologies using W3C standards such as RDF, OWL, and SPARQL.
- Support enterprise knowledge management initiatives by improving metadata quality, taxonomy design, and semantic data structures.
- Work closely with developers, data engineers, AI teams, and business stakeholders to implement and optimize semantic solutions.
- Maintain and evolve ontology models as recent business domains, products, and services are introduced.
- Utilize graph databases and ontology management platforms to manage semantic models and knowledge assets.
- Ensure semantic models align with enterprise standards, governance practices, and business objectives.

Ideal Candidate:

- 8 years of overall experience, including at least 5 years of hands-on experience designing and building semantic ontologies in complex enterprise environments.
- Strong expertise in ontology development, semantic modeling, knowledge graphs, and RDF-based data structures.
- Proven experience designing scalable, intuitive enterprise ontologies that support business processes and AI-driven applications.
- Strong understanding of W3C Semantic Web standards,



including RDF, OWL, and SPARQL.
- Experience translating business requirements into structured ontology and knowledge management solutions.
- Hands-on experience with ontology management tools such as PoolParty, TopQuadrant EDG, GraphDB (Ontotext), or similar platforms.
- Good understanding of graph databases, taxonomies, metadata management, semantic search, and knowledge graph technologies.
- Exposure to Natural Language Processing (NLP) techniques and semantic search optimization will be an added advantage.
- Familiarity with enterprise content management, search, and information retrieval systems is preferred.
- Excellent communication and stakeholder management skills with the ability to collaborate across cross-functional teams.
- Bachelor's or Master's degree in Computer Science, Library Science, Information Management, or a related discipline.
- Must be available to overlap with US business hours for at least 4 hours per day.

Perks, Benefits & Culture:

- Work on enterprise-scale Knowledge Graph and Semantic AI initiatives that power next-generation search and AI capabilities.
- Collaborate with global engineering, AI, and business teams on high-impact data and knowledge management projects.
- Gain exposure to cutting-edge Semantic Web technologies, graph databases, and enterprise AI solutions.
- Opportunity to solve complex enterprise data modeling challenges in a collaborative and innovation-driven environment.
- Continuous learning, professional development, and career growth with emerging technologies in AI, knowledge management, and semantic engineering.
- Competitive compensation, global exposure, and the opportunity to shape enterprise-wide knowledge architecture.

📌 Semantic Data Architect - Ontology Engineering (India)
🏢 TalentXO
📍 India