Project description : Responsibilities : Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar) that model key enterprise data domains and relationships, ensuring a consistent and shared data vocabulary across the organization. This includes collaborating with domain experts to capture real-world concepts and validate that the ontology accurately represents business knowledge.

Knowledge Graph Development: Build and manage enterprise knowledge graphs based on the defined ontologies, linking diverse data sources into a unified graph data model. This involves configuring graph databases or triple stores, populating the knowledge graph with data (RDF triples), and optimizing it for query performance and scalability.

Semantic Querying (SPARQL): Create and optimize SPARQL queries to enable productive retrieval, integration, and analysis of data from the knowledge graph. You will develop semantic queries and endpoints that support advanced search and analytics use cases, making it easier for others to retrieve insights from linked data.

Validation Rules & Data Quality: Implement semantic validation rules and consistency checks (e.g., using SHACL or OWL constraints) to ensure data integrity and quality within the ontology and knowledge graph. You will define and enforce data modelling conventions and business rules so that enterprise data conforms to the ontology's standards and remains interoperable across systems.

Collaboration & Cross-Functional Support: Collaborate with cross-functional teams and stakeholders. For example, partner with AI/ML teams to incorporate the knowledge graph into AI-driven solutions, and team up with business analysts or data stewards to align the semantic models with business needs. You will communicate semantic concepts to non-technical stakeholders, providing training or documentation to ensure adoption of the semantic framework across the organisation.





Standards & Best Practices: Stay current with emerging semantic web standards, tools, and best practices. Continuously improve the semantic architecture by adopting relevant metadata standards and ensuring alignment with industry best practices for ontologies and knowledge graphs. You will also contribute to establishing internal guidelines and best practices for semantic data management, promoting a culture of well-structured, semantically-rich data across the enterprise.

Skills : Must have

Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar).

Semantic Web Proficiency: Strong knowledge of semantic web technologies and standards

specifically, hands-on proficiency with OWL (Web Ontology Language) and RDF (Resource Description Framework) for ontology modelling, as well as SPARQL for querying graph data.

Knowledge Graph Experience: Practical experience building or maintaining knowledge graphs or linked data systems in an enterprise setting.

Data Modelling & Integration Skills: A solid understanding of data modelling principles, data architecture, and integrating heterogeneous data sources. You should be capable of abstracting real-world entities into a semantic schema and mapping relational or NoSQL data to an ontology.

Programming Skills: Proficiency in at least one programming or scripting language (such as Python, Java, or similar)

Nice to have

AI and LLM Integration: Experience working on projects that involve AI agents or large language models, where ontologies or knowledge graphs were used to improve AI performance.

Enterprise System Integration: Proven experience integrating semantic technologies into existing enterprise systems or data platforms.

Tools & Platforms: Hands-on experience with ontology and knowledge graph tools is beneficial.

Other : Languages

English: C1 Advanced

Seniority

Senior

Noida, India

Req. VR-124010

AI/ML

BCM Industry

13/07/2026

Req. VR-124010

📌 Semantic Ai/ml Engineer (Noida)
🏢 Luxoft
📍 Noida