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Knowledge Graph Software Engineer Jobs (NOW HIRING)

GHX

OR

$114K - $152K/yr

The Sr Software Engineer focusing on Knowledge Representation will play a key role in maintaining ... They will leverage graph, table, document and vector store capabilities that interact with AI ...

CYNET SYSTEMS

Knowledge Graph Architect/ Lead

San Jose, CA · On-site

$55 - $60/hr

... Knowledge Graph structures including entities, relationships, hierarchies, and semantic mappings. * 1+ years of experience in mapping business entities into graph-based semantic models. * 1+ years of ...

Geico

Staff Software Engineer (HYBRID)

Bethesda, MD · On-site

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 ...

Geico

Staff Software Engineer (HYBRID)

Dallas, TX · On-site

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 ...

Geico

Staff Software Engineer (HYBRID)

Seattle, WA

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 ...

GEICO

Staff Software Engineer (HYBRID)

Bethesda, MD · On-site

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 ...

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Knowledge Graph Software Engineer information

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$63.5K

$147.5K

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

As of Jun 16, 2026, the average yearly pay for knowledge graph software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Knowledge Graph Software Engineer position, and why are they important?

To thrive as a Knowledge Graph Software Engineer, you need strong expertise in data modeling, graph databases (such as Neo4j or Amazon Neptune), semantic web technologies, and proficiency in languages like Python, Java, or Scala, often supported by a degree in computer science or a related field. Experience with RDF, SPARQL, ontologies, and tools like Protégé or GraphQL is commonly required, and advanced certifications in data engineering can be beneficial. Excellent analytical thinking, problem-solving ability, and collaboration skills help you work effectively with cross-functional teams and translate business requirements into robust graph solutions. These combined technical and interpersonal skills are crucial for building scalable, meaningful knowledge graphs that drive intelligent data-driven applications.

What is a Knowledge Graph Software Engineer job?

A Knowledge Graph Software Engineer designs, builds, and maintains knowledge graphs—structured representations of data that encode relationships between entities. They work with graph databases, ontologies, and data integration techniques to enable intelligent data retrieval and analysis. Their role often involves writing algorithms, implementing ontology-based reasoning, and optimizing graph queries. These engineers collaborate with data scientists, machine learning experts, and domain specialists to enhance data interoperability and usability.

What are the typical day-to-day responsibilities of a Knowledge Graph Software Engineer?

As a Knowledge Graph Software Engineer, your daily responsibilities often include designing and implementing data models, developing and optimizing graph database queries, and integrating diverse data sources into a unified knowledge graph. You’ll collaborate closely with data scientists, product managers, and other engineers to translate business needs into effective graph-based solutions. Additional tasks may involve maintaining existing graph systems, developing tools for data ingestion and quality assurance, and staying updated on the latest graph technologies and best practices. Working in agile, multidisciplinary teams is common, offering opportunities to contribute to both technical architecture and strategic decision-making.

More about Knowledge Graph Software Engineer jobs
What are the most commonly searched types of Knowledge Graph Software Engineer jobs? The most popular types of Knowledge Graph Software Engineer jobs are:
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Knowledge Graph Software Engineer jobs near you
Infographic showing various Knowledge Graph Software Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

Sr Software Engineer - Knowledge Representation (Ontology and ML Engineer)

GHX

OR

$114K - $152K/yr

Other

Posted 5 days ago

Job description

The Sr Software Engineer  focusing on Knowledge Representation will play a key role in maintaining GHX's position at the forefront of AI solutions in Healthcare.   This role will be responsible for applying modern methods for knowledge representation including ontology creation that interact with intelligent systems to meet the challenges GHX faces in assuring affordable quality healthcare for all. 

This Engineer will define, design and curate the key ontological structures needed in the Health Care Supply Chain using data driven, ML and agentic approaches.   They will leverage graph, table, document and vector store capabilities that interact with AI solutions and make sense of diverse internal and external data.  This is a key strategic role in GHX's AI strategy, assuring correct and complete information while supporting explainability and transparency.  The role will primarily be focused on the design and implementation of ontology and graphical structures that interact with other data stores as well as AI solutions including generative and rule based.  They will join a team that is tasked with leading GHX through a transformational change and solidifying its role as the leader in AI in the Healthcare Supply Chain.

Essential Duties:

  • Collaborate with internal and external stakeholders including users, developers, product managers, leadership, etc., to understand needs and challenges and translate these into solutions.
  • Lead, design & develop scalable structures and databases to capture, store and query structured, semi-structured and unstructured data.
  • Lead, design and maintain ontologies and data architectures to represent complex relationships and entities.
  • Mentor junior engineers.
  • Integrate graph solutions with other data stores and technologies.
  • Leverage LLMs/GenAI and rules engines for data I/O and data curation.
  • Multimodal data handling: incorporate text, images, videos, tables, graphs, rules, etc., into the knowledge representation system.
  • Proactively explore new techniques and emerging trends to drive adoption of new solutions.
  • Develop and maintain software tools to support knowledge representation needs.
  • Implement tools for evaluating and monitoring solution performance.
  • Invent and deploy novel solutions with maintainable APIs, MCP servers, to suit stakeholder needs.
  • Adhere to sound software engineering practices.

Competencies:

  • Solid foundational understanding and application of Computer Science principles.
  • Proficiency in knowledge graph technologies (e.g. RDF, LPG, SPARQL, Cypher)
  • Understanding of data modeling, ontology design, data architecture
  • Familiar with LLMs and other machine learning and agentic solutions.
  • Familiar with all steps of SDLC and software development best practices.
  • Excellent software engineering skills including unit testing, modular problem decomposition, multiple solution integration, etc.
  • Fluent with scripting and query languages.
  • Requires minimal to no supervision.

Required Qualifications and Skills:

  • Minimum 8 years working as a software engineer or data scientist, 6 years with a Master's degree.
  • Expertise with one or more Graph query languages (SPARQL, Cypher, Gremlin) and the associated Graph Databases.
  • Experience with Tabular (SQL), Document (NoSQL), and Vector/Semantic databases and their interactions with Graph DBs.
  • Expertise with Python & SQL.
  • Experience with AWS cloud resources (S3, EC2, ECS, Lambda).
  • Experience with Docker or other container services.
  • Specification and creation of APIs and microservices.

Preferred Qualifications and Skills:

  • Computer Science or hard sciences Bachelors degree.
  • Passion to stay on the cutting edge in knowledge representation solutions.
  • Experience with Generative AI solutions.
  • Sense of humor.

Estimated salary range for this position: $114,000 - $152,000

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