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Remote Graph Database Jobs in Texas (NOW HIRING)

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Remote Graph Database information

What is the difference between Remote Graph Database vs Remote Data Analyst?

AspectRemote Graph DatabaseRemote Data Analyst
Required CredentialsKnowledge of graph database systems, certifications like GraphDB or Neo4j certificationsDegree in Data Science, Statistics, or related fields; certifications like Microsoft Data Analyst or Tableau
Work EnvironmentPrimarily working with database management systems, query languages like Cypher, and data modelingAnalyzing datasets, creating reports, using tools like Excel, SQL, Tableau
Employer & Industry UsageTech companies, data-driven organizations, database service providersBusiness intelligence firms, marketing agencies, finance sectors
Search & Comparison IntentUnderstanding technical roles in database managementComparing data analysis roles and skills

Remote Graph Database specialists focus on managing and querying graph databases using specific tools and certifications, while Remote Data Analysts interpret data to provide insights using analytical tools. Both roles are essential in data-driven industries but differ in technical focus and daily tasks.

What job categories do people searching Remote Graph Database jobs in Texas look for? The top searched job categories for Remote Graph Database jobs in Texas are:
What cities in Texas are hiring for Remote Graph Database jobs? Cities in Texas with the most Remote Graph Database job openings:
Infographic showing various Remote Graph Database job openings in Texas as of May 2026, with employment types broken down into 100% Full Time. Highlights an 38% Physical, 1% Hybrid, and 61% Remote job distribution.
AI/ML Engineer

$140K - $220K/yr

Full-time

Posted 12 days ago


Job description

Frontier Technology Inc. (FTI) is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI delivers mission-focused solutions to the Department of Defense/Department of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.


  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a secruity clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.

  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

For this role, the compensation range is $140k-$220k.

*Note: Starting pay will be based on a number of factors and commensurate with the candidate’s residence location, qualifications & experience.

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