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Contract Knowledge Graph Software Engineer Jobs in Charlotte, NC

The Hartford

Staff Software Engineer - AI

Charlotte, NC · On-site

$127K - $191K/yr

Senior Staff Software Engineer - IE07HE We're determined to make a difference and are proud to be ... graph algorithms and knowledge graph. * Experience withversion control systems(e.g., Git)

GDIT

Platform / Software Engineer

Concord, NC · On-site +1

$108K - $147K/yr

API and system-to-system integration (REST, Microsoft Graph API). * Git-based version control and ... Due to U.S. Government contract requirements, only U.S. citizens are eligible for this role.

Broadcom

R&D Software Engineer

Concord, NC · On-site

Manage complex technical dependencies, system interfaces, and API contracts across core product ... Mentor senior and staff engineers in agentic architectures, prompt/context engineering, graph ...

New

GDIT

Platform / Software Engineer, Senior

Concord, NC · Hybrid

$119K - $161K/yr

API and system-to-system integration (REST, Microsoft Graph API). * Git-based version control and ... Due to U.S. Government contract requirements, only U.S. citizens are eligible for this role.

Judge Group, Inc.

Software Engineer

Charlotte, NC · On-site

$69 - $74/hr

The ideal candidate combines strong software engineering fundamentals with deep expertise in GenAI ... Experience with LlamaIndex, Graph RAG, Knowledge Graphs, or advanced retrieval architectures.

Intuit

Staff Data Engineer - Credit Karma

Charlotte, NC · On-site

$202K - $274K/yr

Build agentic systems, semantic search, knowledge graph and personalization to disrupt how ... Strong understanding of software engineering best practices including CI/CD, version control (Git ...

Intuit

Staff Data Engineer - Credit Karma

Charlotte, NC · On-site

$111K - $134K/yr

Build agentic systems, semantic search, knowledge graph and personalization to disrupt how ... Strong understanding of software engineering best practices including CI/CD, version control (Git ...

Judge Group, Inc.

Software Engineer

Charlotte, NC · On-site

$40 - $43/hr

Hybrid (3 days remote, 2 days onsite per week) Duration: 24-Month Contract with Strong Contract-to ... Knowledge of event-driven architectures and messaging technologies such as Kafka. * Experience with ...

AssetMark, Inc.

Platform Software Engineer

Charlotte, NC · On-site

$125K - $142K/yr

Knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes) * hands-on ... Understanding of Microsoft graph APIs Education & Experience * Bachelor's degree in computer ...

AssetMark

Platform Software Engineer

Charlotte, NC · Hybrid

$125K - $142K/yr

Knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes) * hands-on ... Understanding of Microsoft graph APIs Education & Experience * Bachelor's degree in computer ...

Judge Group, Inc.

Software Engineer

Charlotte, NC · On-site

$49 - $53/hr

Contract Client Program: 2026 Q3 CBS Master Bundle Vendors: TEKsystems, Judge Group, Experis ... Knowledge of DevOps practices, infrastructure automation, and cloud-native application development.

Zortech Solutions

Tiger Graph Developer

Charlotte, NC · On-site

$65 - $68/hr

TigerGraph Engineer /Developer Location: Charlotte, NC (5 days onsite) Duration: 12 months Contract Rate: $65-68/hr. on C2C Must Have Skills: Graph database, Tiger Graph or Neo4j or Graph QL or Graph ...

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All JobsContract Knowledge Graph Software Engineer JobsContract Knowledge Graph Software Engineer Jobs in Charlotte, NC

Contract Knowledge Graph Software Engineer information

See Charlotte, NC salary details

$62K

$144.1K

$200.7K

How much do contract knowledge graph software engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for contract knowledge graph software engineer in Charlotte, NC is $144,089.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,200.00 and $169,000.00 per year, depending on experience, location, and employer.

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?

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 Charlotte, NC?

The most popular types of Knowledge Graph Software Engineer jobs in Charlotte, NC are:

What cities near Charlotte, NC are hiring for Contract Knowledge Graph Software Engineer jobs?

Cities near Charlotte, NC with the most Contract Knowledge Graph Software Engineer job openings:

Contract Knowledge Graph Software Engineer jobs near you

Knowledge Graph Engineer

VeeRteq Solutions Inc.

Charlotte, NC • On-site

Contractor

Re-posted 8 days ago

Job description

Role: Knowledge Graph Engineer
Location: Hybrid role for the US PA Area, Dallas, Charolette NC, can also be in NJ but would need to travel to PA.
 
Job Description:
 
Looking for an experienced data engineers with ontology skills. Ontology and Knowledge graph experience. 
 
 
 
Must Have
 
These are the capabilities we cannot compromise on. They reflect information discipline and engineering maturity rather than tool familiarity.
 
 
Data Engineering and Information Management Fundamentals
 
Strong data engineering background with a clear understanding of how data is structured, governed, versioned, and moved across systems. Experience designing durable information models that outlive any single source or implementation. 
Required experience includes AWS data platforms, specifically S3‑based data lakes and AWS‑managed databases. Familiarity with treating data as a long‑lived information asset is essential.
 
 
Information Modeling
 
Ability to organize business concepts clearly, separate meaning from storage, and map real data to conceptual models. Comfort aligning internal models to shared or external standards rather than optimizing only for local schemas.
 
 
Abstract Thinking and Adaptability
 
Comfort working in ambiguity and reasoning from first principles. Ability to learn new modeling approaches, technologies, and standards quickly, adjust assumptions, and refine models as understanding deepens.
 
 
Open Standards Orientation
 
Experience working with open standards in any technology domain, including data formats, APIs, identifiers, or metadata specifications. This may include REST or GraphQL APIs, schema standards, or industry data models. Demonstrated ability to read standards, understand intent, and apply them pragmatically even when the standard is new.
 
 
Engineering Mindset
 
Practical experience integrating conceptual models into real systems. This includes mapping models to data layers, exposing or consuming APIs such as GraphQL, supporting mock or lightweight integrations, and using version control and basic DevOps practices with discipline.
 
 
Communication
 
Ability to explain complex information and data concepts in plain language and connect technical decisions to business outcomes. Clear written and verbal communication is essential. 
Nice to Have
 
These skills accelerate impact but can be learned by the right engineer.
 
 
 
Ontology and Knowledge Graph Technologies
 
Familiarity with ontology and semantic standards such as SKOS, RDF, OWL, and SHACL, or hands‑on experience with knowledge graph technologies and graph databases. Prior depth is helpful but not required if the engineer demonstrates strong information modeling instincts and learning ability.
 
Asset Management Domain Knowledge
 
Understanding of investment products, asset management concepts, and common industry schemas. Domain exposure helps, but strong modeling and engineering skills can bridge gaps.
 
Change Management Awareness
 
Sensitivity to how new standards, APIs, and information structures are adopted within organizations. Appreciation for governance, ownership, and the realities of evolving legacy practices.