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Knowledge Graph Engineer Jobs in Texas (NOW HIRING)

... Knowledge Graph design and implementation -- Neo4j, RDF, SPARQL, and graph-based reasoning for AI applications Strong background in Data Engineering -- ETL/ELT pipelines, data modeling, and ...

Proficient in Knowledge Graph design and implementation - Neo4j, RDF, SPARQL, and graph-based reasoning for AI applications * Strong background in Data Engineering - ETL/ELT pipelines, data modeling ...

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

Senior AI/ML engineer

Richardson, TX · On-site

$94K - $130K/yr

Design and implement Knowledge Graph -based solutions to enhance contextual understanding ... Build advanced prompt engineering workflows and optimize token utilization to improve model ...

Graph DB Consultant

Spring, TX · On-site

$101K - $122K/yr

The role requires deep knowledge of graph and relational database concepts, strong Python and SQL ... developers, and other stakeholders to integrate Cosmos DB with applications and data analytics ...

... and knowledge graph integration. * Ability to collaborate deeply across teams and co-create ... Experience mentoring engineers and helping others grow in AI, LLM, and agent-based system design.

Advance the IMO Health Knowledge Graph and related clinical knowledge assets as foundational ... Partner closely with Engineering, Product, Informatics, Data Science, Security, and Infrastructure ...

Fullstack Software Engineer

Dallas, TX · On-site

$140K - $180K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Through 4Minds's automated data pipeline and proprietary knowledge graph, enterprises can connect ... You'll report to the Engineering Manager and work closely with product, AI research, and ...

Fullstack Software Engineer

Dallas, TX

$140K - $180K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Through 4Minds's automated data pipeline and proprietary knowledge graph, enterprises can connect ... You'll report to the Engineering Manager and work closely with product, AI research, and ...

Advance the IMO Health Knowledge Graph and related clinical knowledge assets as foundational ... Partner closely with Engineering, Product, Informatics, Data Science, Security, and Infrastructure ...

Showing results 21-40

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Infographic showing various Knowledge Graph Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, 1% Temporary, and 3% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

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Re-posted 2 days ago


Job description

AI Engineer | Python + GenAI + Data | 8+ Years Experience 8+ years of engineering experience with Python as the primary language across data, AI, and backend systems Strong proficiency in Generative AI — LLMs, prompt engineering, fine-tuning, and deploying AI models in production Hands-on experience with Context Engineering — designing context windows, retrieval pipelines, and memory management for LLM applications Experience building and optimizing RAG (Retrieval-Augmented Generation) pipelines using vector databases Proficient in Knowledge Graph design and implementation — Neo4j, RDF, SPARQL, and graph-based reasoning for AI applications Strong background in Data Engineering — ETL/ELT pipelines, data modeling, and orchestration tools (Airflow, Prefect, or Dagster) Experience designing Semantic Layers — ontologies, embeddings, and semantic search to connect structured and unstructured data Hands-on building AI Chatbots and conversational agents Proficient with LLM APIs — OpenAI, Anthropic, Gemini, and open-source models (LLaMA, Mistral, Falcon) Experience with vector search, semantic similarity, and embedding strategies (OpenAI Embeddings, Sentence Transformers) Strong understanding of data pipelines — ingestion, transformation, enrichment, and serving layers at scale Familiarity with cloud AI services — AWS Bedrock, Azure OpenAI, GCP Vertex AI Experience with MLOps practices — model versioning, monitoring, and deployment using MLflow, Weights & Biases Proficient with SQL and NoSQL databases alongside graph and vector stores for hybrid data architectures