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Overnight Knowledge Graph Software Engineer Jobs in Texas

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 ...

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: * Neptune specific

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

... Graph QL Knowledge of modern authorization mechanisms, such as JSON Web Token Experience with SPA (single page app) implementation, responsive web design implementation, micro services and API based ...

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 JobsOvernight Knowledge Graph Software Engineer JobsOvernight Knowledge Graph Software Engineer Jobs in Texas

Overnight Knowledge Graph Software Engineer information

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

AspectOvernight Knowledge Graph Software EngineerData Engineer
CredentialsBachelor's or higher in CS, experience with graph databasesBachelor's or higher in CS, experience with data pipelines
Work EnvironmentDeveloping and maintaining knowledge graph systems overnightBuilding and managing data pipelines during regular hours
Industry UsageTech, AI, knowledge management companiesFinance, tech, healthcare, and data-driven industries

The Overnight Knowledge Graph Software Engineer focuses on developing and maintaining knowledge graph systems during overnight shifts, often working with graph databases and semantic data. In contrast, Data Engineers build and manage data pipelines and infrastructure during regular hours. Both roles require strong technical skills, but their focus areas and work schedules differ significantly.

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:
Overnight 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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