- Design and build ontologies (knowledge models) that organize co's business information in a structured way.

- Connect data from different systems so that all information is consistent and easy to understand.

- Create relationships between products, customers, services, and other business data to improve search and AI capabilities.

- Work closely with business teams to understand their requirements and convert them into structured knowledge models.

- Ensure data is organized according to industry standards such as RDF, OWL, and SPARQL.

- Improve enterprise search, analytics, and AI-driven applications by maintaining accurate knowledge - structures.

- Collaborate with developers, data engineers, AI teams, and business stakeholders on knowledge management projects.

- Manage and update ontologies as new products, services, and business information are introduced.

- Support knowledge graph and metadata initiatives to improve data quality and consistency.

- Use graph databases and ontology management tools (where applicable) to maintain semantic data models.

Strong Ontologist Profile :

- Strong Ontologist Profile with deep semantic (RDF) ontology experience in complex enterprise environments.

- Must have 7+ years of total experience, with 5+ years in semantic (RDF) ontology building/structuring for a complex/large enterprises.

- Must have a strong understanding of content and information management, data structures, and semantic metadata extraction.

- Must have strong hands-on experience in taxonomy design, structuring, and lifecycle management.

- Must have strong working experience of at least one ontology/TOMS tool such as PoolParty (Semantic Web), TopBraid/TopQuadrant EDG, or GraphDB (Ontotext).

- Must be familiar with W3C industry standards, including RDF, RDFS, SPARQL and OWL.

- Must have hands-on working experience with at least one graph database such as Neo4j, GraphDB (Ontotext), Neptune, or Stardog.

- Must have practical experience with SHACL for constraint and validation work, alongside SKOS.

- Must have hands-on exposure to a cloud and infrastructure stack, including AWS, Docker, or Kubernetes.

- Must be fluent in English, with strong stakeholder management skills to operate across a complex, multi-team environment.

Mandatory Note :

- Candidate must be comfortable working in US time zones.