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Contract Knowledge Graph Software Engineer Jobs in Texas

Data & Knowledge Graph Architect

Hickory Creek, TX · On-site

$62 - $79.75/hr

Data & Knowledge Graph Architect Job Type: Full Time Experience: 10+ years Job Overview Our client ... Data Engineering: Data Pipeline Design, Batch & Stream Processing, Kafka, Large Data Handling

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 ...

Build Knowledge Graph solutions that transform clients' data architecture. * Design, develop, and ... Prompt engineering, and LLMs for enterprise-scale applications. * You have team lead experience

NAVA Software is looking for an AI Engineer Details: AI Engineer Location: 100% Remote Duration: 6+ ... Knowledge graph implementation (Neo4j preferred). * LLM optimization & improved response handling.

Through 4Minds's automated data pipeline and proprietary knowledge graph, enterprises can connect ... Role Overview As a Full Stack Software Engineer at 4MINDSAI, you will design and build the systems ...

Fullstack Software Engineer

Dallas, TX · On-site

$140K - $180K/yr

Through 4Minds's automated data pipeline and proprietary knowledge graph, enterprises can connect ... Role Overview As a Full Stack Software Engineer at 4MINDSAI, you will design and build the systems ...

As a Full Stack Software Engineer, you will design and build systems that enhance the 4Minds ... the 4MINDS knowledge graph, data pipeline, and AI services • Build and optimize RESTful and ...

Principal Software Engineer (Python)

Austin, TX · On-site +1

$133K - $179K/yr

The hybrid-remote Principal Software Development Engineer leads the design, development, and ... Semantic & Graph Expertise: Deep understanding of Knowledge Representation, Ontologies, and Graph ...

Principal Software Engineer (Python)

Dallas, TX · On-site +1

$133K - $179K/yr

The hybrid-remote Principal Software Development Engineer leads the design, development, and ... Semantic & Graph Expertise: Deep understanding of Knowledge Representation, Ontologies, and Graph ...

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Contract Knowledge Graph Software Engineer information

How does a Contract Knowledge Graph Software Engineer typically collaborate with data scientists and domain experts during a project?

As a Contract Knowledge Graph Software Engineer, you’ll often work closely with data scientists and domain experts to ensure that the knowledge graph accurately represents the underlying data and business logic. Collaboration usually involves regular meetings to clarify requirements, discuss data models, and review results. You may be tasked with translating complex domain concepts into graph structures, while also providing feedback on data quality and integration challenges. This cross-functional teamwork ensures that the final product meets both technical standards and business needs.

What is the difference between Contract Knowledge Graph Software Engineer vs Contract Data Engineer?

AspectContract Knowledge Graph Software EngineerContract Data Engineer
Required CredentialsBachelor's in CS or related, knowledge of graph databases, programming skillsBachelor's in CS, experience with data pipelines, SQL, and cloud platforms
Work EnvironmentTech companies, consulting firms, project-based rolesData-focused teams, cloud environments, analytics projects
Industry UsageAI, semantic web, knowledge managementData warehousing, big data, analytics

The Contract Knowledge Graph Software Engineer primarily focuses on developing and maintaining knowledge graphs using graph databases and semantic technologies, while the Contract Data Engineer concentrates on building data pipelines, managing large datasets, and supporting analytics. Both roles require strong programming skills and are often found in tech-driven industries, but they serve different core functions within data and knowledge management ecosystems.

What is a Contract Knowledge Graph Software Engineer?

A Contract Knowledge Graph Software Engineer is a professional who specializes in designing, developing, and maintaining knowledge graphs on a contract basis. Knowledge graphs are data structures that represent relationships between entities, enabling more effective data integration and semantic search. These engineers often work with graph databases, semantic web technologies, and ontologies to help organizations manage and leverage complex data. Their contract role means they are typically hired for specific projects or fixed periods rather than as permanent employees.

What are the key skills and qualifications needed to thrive as a Contract Knowledge Graph Software Engineer, and why are they important?

To thrive as a Contract Knowledge Graph Software Engineer, you need a strong background in computer science, proficiency in graph databases (such as Neo4j or Amazon Neptune), and experience with knowledge representation and data modeling. Familiarity with programming languages like Python or Java, as well as tools for semantic web technologies (RDF, SPARQL), is typically required. Strong problem-solving skills, adaptability, and effective collaboration are essential soft skills in this role. These competencies ensure efficient design and implementation of complex knowledge graphs, enabling organizations to unlock valuable insights from their data.
What are the most commonly searched types of Knowledge Graph Software Engineer jobs in Texas? The most popular types of Knowledge Graph Software Engineer jobs in Texas are:
Consultant Machine Learning & Knowledge Graph Engineer

Consultant Machine Learning & Knowledge Graph Engineer

Dell, Inc.

Round Rock, TX • On-site

Full-time

Posted 13 hours ago


Job description


Consultant Machine Learning & Knowledge Graph Engineer
Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What's more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.
Join us to do the best work of your career and make a profound impact as Consultant ML & KG Engineer on our growing and dynamic team in Round Rock, Texas.
What you'll achieve
Lead the architecture, development, and deployment of enterprise scale ML solutions across Dell's global ecosystem. Drive MLOps standards, build production grade ML services, and collaborate across engineering, product, and platform teams to enable AI at scale.scale ML solutions across Dell's global ecosystem. As a Consultant Machine Learning & Knowledge Graph Engineer, you will play a pivotal role in advancing our AI and ML capabilities and creating Enterprise wide KG marketplace and Ontology layouts. You will be responsible for designing, building, and operationalizing machine learning systems, including next generation agentic and GenAI powered applications. You will drive and execute our broader AI/ML strategy. You will also be responsible to architect production-grade Knowledge Graph platforms, design semantic data layers that power Agentic AI, and drive the convergence of graph technologies with large-scale data engineering ecosystems. This role demands a rare combination of deep graph expertise, distributed systems mastery, and strategic business influence. You will work deeply across data pipelines, model development, optimization, and production deployment to deliver scalable, high performance ML solutions.
You will
  • Lead the end-to-end Agentic lifecycle-from conceptualizing, prototyping and driving delivery with engineering teams and design and build autonomous AI agents, ML systems, pipelines, and inference services.
  • Work with business leads to imagine agentic products and drive accelerated delivery through Spec Driven Development and implement MLOps practices including CI/CD, model monitoring, drift detection, and automated retraining.
  • Collaborate with Data Engineering and Platform teams to ensure data, infrastructure, and governance readiness along with providing technical leadership while integrating emerging AI/ML technologies and managing production incidents.
  • Design, build, and scale enterprise Knowledge Graph platforms using Neo4j and/or Stardog, establishing graph-native data models that enable entity resolution, relationship discovery, and semantic reasoning across business domains.
  • Define and govern enterprise ontologies (OWL 2), taxonomies, and semantic schemas that provide a unified, machine-interpretable view of Dell's data assets, ensuring consistency, reusability, and inferencing capability
  • Architect graph-backed Retrieval-Augmented Generation (RAG) systems, tool-calling interfaces, and dynamic prompt-to-graph query pipelines that fuel autonomous AI agent decision-making with deterministic, explainable knowledge

Take the First Step Towards Your Dream Career
Every Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:
Essential Requirements:
  • 12+ years of experience delivering complex AI/ML or applied science systems, including deep learning, machine learning, and LLM-based solutions.
  • Advanced Python expertise with strong knowledge of ETL pipelines (Airflow preferred) and modern data-warehousing concepts.
  • Graph Architecture Mastery: Extensive hands-on experience designing and operating production-grade graph systems using Neo4j (Cypher, GDS, APOC, AuraDB, Causal Clustering) and/or Stardog (SPARQL, OWL 2 reasoning, Virtual Graphs, SHACL validation)
  • Distributed Systems and Data Scale: Expert-level command over PySpark, Kafka, data lakehouses (Apache Iceberg, Delta Lake), and enterprise orchestration (Airflow), with proven ability to integrate these with graph ecosystems
  • Strong software engineering background with hands-on experience in AI frameworks, cloud environments, and domains such as ML, NLP, IR, recommender systems, and LLMs and proven experience with Docker, Kubernetes, and major cloud platforms (AWS/GCP/Azure), including training, fine-tuning, and applying LLMs for agentic AI applications.

Desirable Requirements
  • PhD or Master's degree in Technology, Computer Science, Machine Learning or equivalent quantitative field
  • Familiarity leveraging graph-based techniques, semantic search, hybrid search systems, and implementing solutions that combine traditional IR methods with machine learning models to enhance search relevancy accuracy and efficiency. Familiarity with large scale data handling when dealing with telemetry systems.

DELL logo

About DELL

Sourced by ZipRecruiter

Dell Technologies helps organizations and individuals build a brighter digital tomorrow. Our company is made up of more than 150,000 people, located in over 180 locations around the world. We're proud to be a diverse and inclusive team and have an endless passion for our mission to drive human progress.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Round Rock, TX, US

Year founded

1984