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Vrinda International

Vrinda International

KNOWLEDGE ENGINEER – AWS & KNOWLEDGE GRAPH

Bengaluru, INفي الموقعدائمدوام كامل

تم النشر في 5 سبتمبر 2026

تم نشر هذه الوظيفة باللغة EN

HIRING | KNOWLEDGE ENGINEER – AWS & KNOWLEDGE GRAPH

Location: Bengaluru

Experience: 6-8 years

Role: Knowledge Engineer / Senior Engineer

Work Mode: Bengaluru, BDC7A

Education: 15 Years Full-Time Education

CTC : 17 LPA

ROLE OVERVIEW

We are looking for a Knowledge Engineer experienced in AWS, Knowledge Graphs, Semantic AI, Ontologies and AI/LLM solutions to design and lead enterprise-scale knowledge engineering initiatives.

MUST-HAVE SKILLS

AWS Big Data

Knowledge Graph & Semantic Modeling

Amazon Neptune / Neo4j / Graph Databases

RDF, SPARQL, OWL, SHACL, LPG

Ontology, Taxonomy & Schema Management

Python, SQL, PySpark

AWS S3, Glue, Lambda, EMR, Redshift, Athena

OpenSearch, Bedrock, SageMaker

Data Engineering & ETL/ELT Pipelines

LLM Grounding, RAG & Semantic Search

KEY RESPONSIBILITIES

  • Design scalable AWS-based Knowledge Graph and semantic solutions
  • Build graph ingestion pipelines, semantic layers, vector integrations and RAG solutions
  • Develop ontologies, schemas, taxonomies and knowledge curation frameworks
  • Collaborate with architects, AI engineers, data engineers and business stakeholders
  • Lead technical workstreams and mentor engineering teams
  • Support solution shaping, client discussions and pre-sales activities

Good to Have: AWS Certifications, BFSI/Healthcare/Retail/Telecom/Manufacturing domain experience, Azure/GCP exposure and client-facing consulting experience

ملخص الدور

نوع الوظيفة

دوام كامل

المهارات المطلوبة

Knowledge Graph & Semantic ModelingOntology, Taxonomy & Schema ManagementRDF, SPARQL, OWL, SHACL, LPGGraph Databases (Amazon Neptune / Neo4j)Python, SQL, PySparkAWS Big Data & Services (S3, Glue, Lambda, EMR, Redshift, Athena)OpenSearch, AWS Bedrock, SageMakerData Engineering & ETL/ELT PipelinesLLM Grounding, Retrieval-Augmented Generation (RAG) & Semantic SearchVector integrations and embedding-based vector searchDesigning and implementing graph ingestion pipelines and semantic layersSolution Architecture for scalable AWS-based knowledge graph systemsTechnical leadership, leading workstreams and mentoring engineering teamsClient-facing solution shaping, pre-sales and stakeholder collaboration

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