Knowledge Graph Expert – Graph Integration with AI

JOB TITLE: Knowledge Graph Expert – Graph Integration with AI

JP ID: DLTJP00062611

Client: Deloitte USI

Experience: 4–8 Years Overall

Relevant Experience: Minimum 2+ Years in Graph-AI Integration

Work Location: Bengaluru / Hyderabad / Chennai / Pune

Shift Timing: 11:00 AM – 8:00 PM

Interview Process: 2 Rounds

Client Round: Not Required

MANDATORY SKILLS

• Hands-on experience in Knowledge Graph design, data modeling, and development.

• Strong experience with graph databases such as Neo4j, Amazon Neptune, TigerGraph, Stardog, or GraphDB.

• Proficiency in graph query languages, including GraphQL, Cypher, SPARQL, and Gremlin.

• Strong programming experience in Python.

• Ability to design, build, and optimize scalable graph-based solutions and integrate them with enterprise applications.

• Cloud platform experience is mandatory.

GOOD-TO-HAVE SKILLS

• Graph integration with AI.

• Healthcare domain experience.

• Experience with ontology design, RDF/OWL, and taxonomy development.

• Experience with entity resolution, Named Entity Recognition (NER), and relation extraction.

• Familiarity with graph libraries such as RDFLib, NetworkX, and Apache Jena.

• Familiarity with data pipeline tools such as Apache Airflow and Spark.

ROLE OVERVIEW

Design, build, and maintain scalable knowledge graph solutions that support search, recommendations, data integration, and AI/ML applications. Transform disparate data sources into connected, queryable knowledge using data modeling, semantic technologies, and software engineering.

KEY RESPONSIBILITIES

• Design and implement ontologies, taxonomies, and schemas using RDF/OWL and property graphs.

• Build and maintain knowledge graph pipelines for entity extraction, resolution, linking, and enrichment from structured and unstructured data.

• Develop and optimize graph queries using SPARQL, Cypher, Gremlin, or similar query languages.

• Integrate knowledge graphs with search, recommendation engines, and LLM-based systems, including Retrieval-Augmented Generation (RAG).

• Collaborate with data engineers, ML engineers, and domain experts to identify data sources and graph-based use cases.

• Ensure data quality, consistency, and governance, including entity deduplication and conflict resolution.

• Evaluate and select appropriate graph databases and tools.

• Monitor and improve graph performance, scalability, and reliability in production.

• Stay updated on semantic web technologies, graph ML, and knowledge representation.

• Document data models, pipelines, and best practices for internal stakeholders.

REQUIRED TECHNICAL SKILLS

• Knowledge graph development and semantic data modeling.

• Graph databases: Neo4j, Amazon Neptune, TigerGraph, Stardog, or GraphDB.

• Query languages: GraphQL, Cypher, SPARQL, and Gremlin.

• Ontology design, RDF/OWL, and taxonomy development.

• Python or Java programming and graph libraries.

• Entity resolution, NER, and relation extraction.

• Data pipeline tools and workflows such as Apache Airflow and Spark.

• Strong analytical and problem-solving skills with attention to data quality.

IMPORTANT SCREENING POINTS

• Overall experience must be 4–8 years.

• Minimum 2+ years of relevant hands-on Graph-AI integration experience.

• Cloud platform experience is mandatory.

• Prioritize candidates with hands-on Knowledge Graph development and enterprise integration experience.

Pay: Up to ₹2,100,000.00 per year

Work Location: Hybrid remote in Bangalore City, Bengaluru, Karnataka