KNOWLEDGE ENGINEER – AWS & KNOWLEDGE GRAPH

Vrinda International; Bengaluru; On-site; INR 3,000,000 - 4,600,000; Full time

Job summary

Vrinda International is seeking a Knowledge Engineer to design and implement AWS-based Knowledge Graphs, semantic models, ontologies, and AI-enabled data solutions in Bengaluru. You will handle graph ingestion, semantic modeling, LLM grounding, vector search, and GenAI integration.

The role requires hands-on expertise with AWS services, graph databases, RDF/OWL, and Python, SQL, PySpark. Collaboration with delivery teams and clients is essential for scalable AI pipelines.

Qualifications

• 15 years of full-time education completed.
• Experience building Knowledge Graphs and semantic pipelines.
• Strong AWS data engineering and modeling skills.

Responsibilities

• Design and develop AWS-based Knowledge Graph solutions
• Build ontology, schema, mapping and semantic pipelines
• Develop graph, vector search and LLM grounding solutions
• Integrate AI/GenAI capabilities with enterprise systems
• Build scalable data pipelines for AI applications
• Collaborate with architects, engineers, clients and delivery teams
• Support POCs, demos, reusable assets and solutioning

Skills

Amazon Neptune

AWS S3

Glue

Lambda & Step Functions

OpenSearch

SageMaker

Bedrock

Knowledge Graph

Semantic Modeling

Ontology

Schema & Taxonomy

Python

SQL

PySpark

RDF

SPARQL

SHACL / OWL

Neo4j

Stardog

LLM

RAG

Vector Search

Generative AI

Graph RAG

Education

15 Years Full-Time Education

Tools

Python

SQL

PySpark

Job description

KNOWLEDGE ENGINEER – AWS & KNOWLEDGE GRAPH

Job Description

HIRING | KNOWLEDGE ENGINEER – AWS & KNOWLEDGE GRAPH

Experience: 8-12 YEARS

Education: 15 Years Full-Time Education

ROLE OVERVIEW

We are looking for a skilled Knowledge Engineer to build scalable Knowledge Graph, Semantic Layer, Ontology, and AI-enabled data solutions using AWS. The role involves hands-on work across graph ingestion, semantic modeling, LLM grounding, vector search, and AI solutions.

MUST-HAVE SKILLS

• Amazon Neptune
• AWS S3, Glue, Lambda & Step Functions
• OpenSearch, SageMaker & Bedrock
• Knowledge Graph & Semantic Modeling
• Ontology, Schema & Taxonomy Management
• Python, SQL & PySpark
• RDF, SPARQL, SHACL / OWL
• Neo4j / Stardog / Amazon Neptune
• LLM, RAG, Vector & Semantic Search
• Graph RAG / Generative AI

KEY RESPONSIBILITIES

• Design and develop AWS-based Knowledge Graph solutions
• Build ontology, schema, mapping and semantic pipelines
• Develop graph, vector search and LLM grounding solutions
• Integrate AI/GenAI capabilities with enterprise systems
• Build scalable data pipelines for AI applications
• Collaborate with architects, engineers, clients and delivery teams
• Support POCs, demos, reusable assets and solutioning