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Contract Knowledge Graph Software Engineer Jobs in Texas

Spiceorb

Knowledge Graph Engineer

Frisco, TX

Knowledge Graph Engineer Location: Frisco, TX and Atlanta, GA (Onsite) Duration ... Contract Must: * Graph DB (Neptune OR Neo4j OR Tiger Graph) * Gremlin OR Cypher Good to have:

Tekwissen

Knowledge Graph Engineer

Frisco, TX · Hybrid

Knowledge Graph Engineer Location: Atlanta GA / Frisco TX Duration: 6 Months Job Type: Temporary Assignment Work Type: Hybrid : About the Role: * We are looking for an experienced Knowledge Graph ...

Geico

Staff Software Engineer (HYBRID)

Dallas, TX

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 ...

NAVA Software Solutions

AI Engineer -Remote

Houston, TX · On-site +1

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.

Keylent Inc

Sr Software Engineer

Plano, TX · On-site

$117K - $155K/yr

Sr Software Engineer TECHM-JOB-22462 Contract Location: Plano TX Skill ADO.NET Experience: 10+ ... Knowledge of NET Core with C# Familiarity with RESTful APIs, Graph QL Knowledge of modern ...

K-Tek Resourcing LLC

Neo4j Graph Database Engineer

Austin, TX · On-site

$113K - $136K/yr

Experience with graph analytics, graph algorithms, and knowledge graphs. * Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. * Experience with data engineering and data ...

Cotality

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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All JobsContract Knowledge Graph Software Engineer JobsContract Knowledge Graph Software Engineer Jobs in Texas

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:
Contract Knowledge Graph Software Engineer jobs near you

Knowledge Graph Engineer

e-IT Professionals Corp.

Frisco, TX

Other

Posted 11 days ago

Job description

Job Title: Knowledge Graph Engineer

Location: Frisco TX or Atlanta, GA
Mode: Contract

Should work any of these companys :: Google Meta Amazon Apple Netflix Microsoft Nvidia Salesforce Oracle IBM Intel Cisco Adobe Palantir Snowflake Databricks Twitter / X LinkedIn Uber Airbnb

Must: - Graph DB (Neptune OR Neo4j OR TigerGraph) - Gremlin OR Cypher
Good to have: - Neptune specific - Flink - Embeddings
About the Role
We are looking for an experienced Knowledge Graph Engineer to design, build, and scale a production-grade property graph platform that powers customer segmentation, device intelligence, and household-level insights. You will own the full lifecycle from schema design and bulk ingestion to real-time CDC pipelines and graph embedding working closely with the segment engine team to deliver high-performance traversal queries and ML-ready embeddings at scale.
Key Responsibilities
Schema Design: Architect the property graph schema defining node types Customer, Device, Account, Plan, Offer and edge types HAS_DEVICE, ON_PLAN, SHARES_HOUSEHOLD, SIMILAR_TO ensuring optimal cardinality and partition key design for scale.
Bulk Load Pipeline: Build and validate the initial bulk load job across the ingestion stack (e.g., Delta Lake S3 staging Neptune bulk loader or equivalent technology).
Real-Time CDC Pipeline: Implement a change data capture pipeline (e.g., Cosmos DB Change Feed Kafka Flink Neptune writer) with an end-to-end lag target of <60 seconds.
Query Development: Write and optimize Gremlin traversal queries for household segmentation, device-sharing patterns, and account-linked segmentation use cases.
Index Strategy: Design vertex-centric indexes and leverage Neptune Analytics HNSW for embedding-based similarity lookups.
Graph Embeddings: Build a Node2Vec embedding pipeline (SageMaker or Databricks) and load SIMILAR_TO edges to support ML-driven similarity features.
Documentation: Document schema definitions, traversal patterns, and query performance benchmarks for consumption by the segment engine team.
Must-Have Skills & Qualifications
4+ years of graph database engineering experience with production Gremlin / TinkerPop expertise.
AWS Neptune or equivalent cloud graph database bulk loader operations, instance sizing, HA configuration, and VPC networking.
Apache Kafka and Apache Flink for CDC pipeline design and implementation.
Property graph data modelling entity resolution, edge cardinality, and partition key design.
Graph traversal performance profiling at scale (100M+ nodes).
Nice-to-Have Skills
Graph embedding algorithms Node2Vec, GraphSAGE, or similar.
Neptune Analytics experience for graph analytics workloads.
Neo4j migration or comparative architecture experience (trade-offs vs. Neptune at scale).
Python (gremlinpython) and Java traversal source authoring.
AWS SageMaker or Azure Databricks for embedding model training.
What We Offer
Opportunity to architect and own a greenfield knowledge graph platform at enterprise scale.
Work with cutting-edge graph and ML technologies across AWS, Kafka, Flink, and SageMaker ecosystems.
Collaborate with data engineering, ML, and product teams to drive real customer and business impact.
Competitive compensation, flexible work arrangements, and a culture of continuous learning.

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