Graph Platform

We are looking for a highly skilled Knowledge Graph Engineer (Senior Consultant / Equivalent) to design, develop, and optimize enterprise-scale Knowledge Graph and AI-powered data intelligence solutions. The ideal candidate will have strong expertise in Python, Azure cloud services, Neo4j, PostgreSQL, LangChain, LangGraph, and Retrieval-Augmented Generation (RAG) architectures. You will be responsible for building scalable data pipelines, enabling semantic intelligence through knowledge graphs, developing AI-powered search and discovery solutions, and integrating GenAI workflows that transform enterprise data into actionable insights. This role requires a strong blend of data engineering, graph technologies, cloud-native development, and AI/ML expertise.

• Design, develop, and maintain scalable data pipelines using Python within Azure cloud environments.
  
• Build and manage data ingestion and transformation workflows for structured and unstructured data sources.
  
• Orchestrate data pipelines for seamless integration with graph databases and relational databases.
  
• Develop and enhance enterprise Knowledge Graph solutions to support semantic intelligence and AI-driven insights.
  
• Implement GenAI-powered NLP workflows using LangChain and LangGraph for entity extraction, relationship mapping, and metadata enrichment.
  
• Design, optimize, and maintain data models within Neo4j AuraDB and PostgreSQL environments.
  
• Enable semantic enrichment, graph analytics, intelligent search, and enterprise knowledge discovery.
  
• Develop and maintain RESTful APIs using FastAPI or Flask for:
  • Data Ingestion
    
  • Data Retrieval and Querying
    
  • Workflow Orchestration
    
• Design and enhance Retrieval-Augmented Generation (RAG) pipelines for intelligent search and contextual insights.
  
• Integrate LangGraph workflows with Neo4j Cypher query generation for advanced graph-based querying capabilities.
  
• Support AI-powered reporting, automated insights generation, and knowledge discovery initiatives.
  
• Collaborate with DevOps teams to deploy and manage containerized applications on Azure Kubernetes Service (AKS).
  
• Implement autoscaling and performance optimization solutions using KEDA.
  
• Support CI/CD implementation, deployment automation, and cloud-native operational excellence.
  
• Ensure compliance with enterprise security, governance, and regulatory standards.
  

• 5–6 years of experience in Data Engineering, Knowledge Graphs, AI/ML Engineering, or related domains.
  
• Strong proficiency in Python for backend development, data engineering, and AI workflows.
  
• Hands-on experience with Azure cloud services, including:
  • Azure Data Factory
    
  • Azure Functions
    
  • Azure Kubernetes Service (AKS)
    
• Experience building scalable data ingestion, processing, and transformation pipelines.
  
• Strong expertise in LangChain and LangGraph frameworks.
  
• Experience working with Knowledge Graph technologies and graph databases, particularly Neo4j AuraDB.
  
• Strong knowledge of PostgreSQL and relational database design principles.
  
• Experience developing RESTful APIs using FastAPI or Flask.
  
• Strong understanding of semantic data modeling, metadata management, and graph analytics.
  
• Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
  
• Knowledge of AI-powered search, intelligent retrieval, and enterprise knowledge management solutions.
  
• Experience with containerized applications and cloud-native architectures.
  
• Strong analytical, troubleshooting, and problem-solving skills.