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Ontology Expert & Knowledge Graph Engineer

ID de Puesto
471392
Publicado desde
22-Jul-2025
Ámbito de trabajo
Information Technology
Empresa
Siemens Healthcare Private Limited
Nivel de experiencia
Profesional Experimentado
Tipo de jornada
Jornada completa
Modalidad de trabajo
Híbrido (remoto/oficina)
Tipo de contrato
Indefinido
Ubicación(es)
  • Bangalore - Karnataka - India
We are seeking a highly skilled Ontology Expert & Knowledge Graph Engineer with expertise in ontology development and knowledge graph implementation. This role will be pivotal in shaping our data infrastructure and ensuring accurate representation and integration of complex data sets. You will leverage industry best practices to design, develop, and maintain ontologies, semantic and syntactic data models, and knowledge graphs that drive data-driven decision-making and innovation within the company.

Job Purpose:
The role of Ontology & Knowledge Graph / Data Engineer is to design, develop, implement, and maintain enterprise ontologies in support of Organizations Data Driven Digitalization strategy.

This role combines architecture ownership with hands-on engineering: you will model ontologies, stand up graph infrastructure, build semantic pipelines, and expose graph services that power search, recommendations, analytics, and GenAI solutions for our organization.

Seeking highly skilled motivated expertise to drive the development and shape the future of enterprise AI by designing and implementing large-scale ontologies and knowledge graph solutions. You’ll work closely with internal engineering and AI teams to build scalable data models that enable advanced reasoning, semantic search, and agentic AI workflows.

Key Responsibilities:

1. Ontology Development:
  • Design and apply ontology principles to improve semantic reasoning and data integration, ensuring alignment with business requirements and industry standards.
  • Collaborate with domain experts, product managers and customers to capture and formalize domain knowledge into ontological structures and vocabularies & improve data discoverability.
  • Develop and maintain comprehensive ontologies to model various business entities, relationships, and processes.
  • Integrate Semantic Data Models with existing data infrastructure and applications
2. Knowledge Graph Implementation & Data Integration:
  • Design and build knowledge graphs based on ontologies.
  • Create\Build Knowledge Graph based on the data from multiple sources while ensuring data integrity and data consistency.
  • Collaborate with data engineers for data ingestion and ensure smooth integration of data from multiple sources
  • Administer and maintain graph database solutions, including both Semantic and Property Graphs
  • Utilize knowledge graphs to enable advanced analytics, search, and recommendation systems.
3. Data Quality and Governance:
  • Ensure the quality, accuracy, and consistency of ontologies, and knowledge graphs.
  • Define and implement data governance processes and standards for ontology development and maintenance.
4. Collaboration And Communication:
  • Collaborate with internal engineering teams to align data architecture with Gen AI capabilities
  • Leverage on AI techniques by aligning knowledge models with RAG pipelines and agent orchestration
  • Work closely with data scientists, software engineers, and business stakeholders to understand their data requirements and provide tailored solutions.
  • Research and Innovation: Stay up to date with the latest advancements in the field of NLP, LLM and machine learning and proactively identify opportunities to leverage new technologies for improved solutions.
Experience:
  • 4–6 years of industrial experience in AI [OR] Data Science [OR] Data Engineering.
  • 2–3 years of hands-on experience building ontologies and knowledge systems.
  • Proficiency with graph databases such as Neo4j, GraphDB [RDF based].
  • Understanding of semantic standards like OWL, RDF, W3C and property graph approaches.
  • Familiarity with Gen AI concepts including retrieval-augmented generation and agent-based AI.
Required Knowledge/Skills, Education, and Experience:
  • Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, or a related field, or a specialization in natural language processing is preferred.
  • Strong knowledge of semantic web technologies, including RDF, OWL, SPARQL, and SHACL.
  • Proficiency in Python and other programming languages used for data engineering.
  • Experience with NLP and GEN AI based Frameworks [Langchain, Langgraph]
  • Good working project experience in cloud computing i.e., AWS/ Azure/GCP cloud Services including VPCs, EBS, ALBs, NLBs, EC2, S3, and so on so forth.