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Knowledge Graph Engineer Jobs in Texas (NOW HIRING)

GEICO is seeking an experienced Staff Software Engineer to join our Knowledge Graph and Content Generation engineering group. This is a high-impact team focused on scaling GEICO's intelligent content ...

AI Engineer Location: 100% Remote Duration: 6+ month contract-to-hire Requirement: * Implemented ... Knowledge graph implementation (Neo4j preferred). * LLM optimization & improved response handling.

Data Engineer - AI

Dallas, TX · On-site

$113K - $136K/yr

Work alongside engineers building ontology layers, semantic layers, and knowledge graph systems * Help structure and operationalize datasets for AI-driven applications * Support vector database ...

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Knowledge Graph Engineer information

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Infographic showing various Knowledge Graph Engineer job openings in Texas as of May 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution.
Lead AI Engineer (Knowledge Graph / Ontology & Agentic AI)

Lead AI Engineer (Knowledge Graph / Ontology & Agentic AI)

Anblicks

Dallas, TX

$101K - $134K/yr

Other

Posted 17 days ago


Job description

Job Description Lead AI Engineer (Knowledge Graph / Ontology & Agentic AI)

Location: Dallas, TX

Role Summary

Seeking a Lead AI Engineer with strong expertise in Knowledge Graph (KG), Ontology modeling, and Generative AI (LLMs, Agentic AI) to design and scale a Customer Knowledge Graph platform using Neo4j and App Orchid. The role will lead AI product/platform development, enabling relationship intelligence, Customer 360 insights, and AI-driven decisioning.

Key Responsibilities

Knowledge Graph & Ontology (Neo4j / App Orchid)

  • Design and implement ontology models and semantic frameworks
  • Build and scale Customer Knowledge Graph using Neo4j and App Orchid
  • Develop entity resolution, relationship mapping, and enrichment pipelines
  • Write and optimize graph queries (Cypher) for analytics and insights
  • Manage performance, scalability, and governance of KG platform

AI & Agentic AI Development

  • Architect and implement Agentic AI and multi-agent systems
  • Leverage LLMs and RAG with Knowledge Graph for contextual intelligence
  • Enable capabilities such as:
    • Customer 360 insights
    • Relationship discovery & scoring
    • Natural language querying (Graph/SQL agents)
  • Drive end-to-end AI lifecycle (design deploy optimize)

Data Engineering & Integration

  • Build scalable pipelines to integrate enterprise data into KG
  • Implement customer identity resolution and data quality frameworks
  • Design APIs for application and AI model integration

Leadership & Platform Ownership

  • Lead AI platform architecture and roadmap
  • Mentor engineering teams and enforce best practices
  • Drive AI-first SDLC adoption and enterprise scaling
  • Collaborate with business, data science, and engineering stakeholders

Required Skills

  • Knowledge Graph & Ontology: RDF, OWL, semantic modeling
  • Graph Platforms: Strong hands-on with Neo4j and App Orchid
  • Graph Querying: Cypher (mandatory)
  • AI/GenAI: LLMs, RAG, Agentic AI (CrewAI/LangGraph)
  • Programming: Python (AI + data engineering)
  • Data Engineering: Spark, Kafka, Airflow (or equivalent)
  • Cloud: AWS / Azure
  • MLOps/DevOps: CI/CD, scalable system design

Preferred Skills

  • Customer 360 / Customer Data Platforms
  • Graph analytics (community detection, centrality)
  • Graph visualization tools
  • Exposure to GNNs
  • Docker / Kubernetes

Leadership Expectations

  • Own AI product/platform delivery end-to-end
  • Define technical roadmap and architecture strategy
  • Drive enterprise AI adoption with business impact (revenue, engagement)