Ontology & Semantic Modeler

• Job Title: Ontology & Semantic Modeler
• Experience: 6–8+ Years
• Location: Remote/ Bengaluru
• Notice Period: Immediate Joiners Preferred

Job Overview

• We are looking for an experienced Knowledge, Ontology
• & Semantic Modeler to design and develop enterprise ontologies,
• semantic models, and knowledge graphs. The ideal candidate will establish
• consistent business meaning across multiple data sources and build semantic
• foundations that enable AI-powered knowledge retrieval, reasoning, and
• enterprise intelligence.
• The candidate should have strong expertise in ontology
• engineering, semantic data modeling, knowledge representation, and semantic
• technologies, with an understanding of modern AI architectures, including Large
• Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph RAG.

Key Responsibilities

Design

and develop enterprise ontologies, taxonomies, knowledge graphs, and

semantic data models.

Define

business concepts, entities, relationships, hierarchies, rules, and

business metrics.

Develop

semantic mappings between source systems, canonical data models, and

business ontologies.

Implement

entity resolution, semantic enrichment, ontology alignment, and

relationship discovery.

Build

enterprise semantic layers to support business queries, knowledge

retrieval, and AI-driven applications.

Apply

knowledge representation, inference, and rule-based reasoning techniques.

Establish

semantic governance, data validation, lineage, and version management

practices.

Develop

semantic queries and support natural language-to-structured query mapping.

Collaborate

with business stakeholders, data architects, data engineers, and AI teams

to translate domain knowledge into reusable semantic models.

Support

AI applications through structured knowledge foundations, semantic

retrieval, and knowledge graph integration.

Required Technical Skills

• Ontology Engineering & Knowledge Graphs

Strong

hands-on experience with RDF, RDFS, OWL, SKOS, SPARQL, JSON-LD, and SHACL.

Expertise

in ontology engineering, taxonomy design, and knowledge graph development.

Experience

with graph databases such as Neo4j, Amazon Neptune, or GraphDB.

• Semantic Modeling & Reasoning

Strong

understanding of semantic data modeling, concept mapping, and ontology

alignment.

Experience

in entity resolution, relationship modeling, and semantic enrichment.

Knowledge

of inference engines, knowledge representation, and rule-based reasoning.

Experience

defining business glossaries, semantic definitions, business metrics, and

dimensional hierarchies.

Ability

to design semantic queries and map natural language queries to structured

data queries.

• Data Engineering & AI Technologies

Good

understanding of SQL, data modeling, metadata management, and data

integration.

Familiarity

with enterprise semantic layers and semantic data architecture.

Understanding

of LLMs, RAG, Graph RAG, hybrid retrieval, and AI-powered knowledge

retrieval.

Python

programming and experience with semantic web libraries are desirable.

Preferred Qualifications

Hands-on

experience building enterprise semantic layers and reusable knowledge

models.

Experience

developing knowledge foundations for AI-powered enterprise applications.

Exposure

to integrating knowledge graphs with LLM-based applications and retrieval

pipelines.

Strong

analytical, problem-solving, communication, and stakeholder collaboration

skills.

Requirements

Ontology

• Engineering, Semantic Data Modeling, Knowledge Graph Development, Semantic
• Architecture, or Enterprise Data
• Architecture who have hands-on experience with
• semantic web standards and AI-enabled knowledge systems are encouraged to
• apply.
• Keywords: Ontology Engineering, Semantic Modeling, Knowledge Graph, RDF, RDFS, OWL, SKOS,
• SPARQL, JSON-LD, SHACL, Neo4j, GraphDB, Amazon Neptune, Semantic Layer, Entity
• Resolution, Metadata Management, Python, SQL, LLM, RAG, Graph RAG, Knowledge
• Representation