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Remote Knowledge Graph Software Engineer Jobs (NOW HIRING)

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.

Principal Software Engineer, AI

$138K - $185K/yr

Remote - US Clari + Salesloft are building the next era of enterprise revenue - one where teams ... This includes a knowledge graph, RAG and retrieval systems, and the access control and governance ...

The Content Knowledge Graph team within Data Science & Engineering equips scientists, engineers ... We are looking for a Full Stack Software Engineer to own and scale our online data systems while ...

Develop graph traversal capabilities using Apache TinkerPop, Gremlin, JanusGraph, or similar ... Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies ...

Software Engineer

New York, NY · On-site +1

$220K - $230K/yr

Any amount of experience utilizing graph theory to create interactive data visualization user ... Remote working is permitted on occasion but office attendance is expected. Salary range: $220,000 ...

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Remote Knowledge Graph Software Engineer information

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$63.5K

$147.5K

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

As of Jul 14, 2026, the average yearly pay for remote 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 as a Remote Knowledge Graph Software Engineer, and why are they important?

To thrive as a Remote Knowledge Graph Software Engineer, you need expertise in graph data modeling, proficiency in programming languages such as Python or Java, and a solid understanding of semantic web technologies, often backed by a degree in computer science or a related field. Familiarity with graph databases like Neo4j or Amazon Neptune, query languages such as SPARQL or Cypher, and experience with knowledge representation frameworks are typically required. Strong problem-solving abilities, effective remote communication, and self-motivation are crucial soft skills for this role. These skills ensure the engineer can design, implement, and maintain complex knowledge graph systems, enabling intelligent data connections and supporting scalable, collaborative remote work environments.

How does a Remote Knowledge Graph Software Engineer typically collaborate with cross-functional teams given the distributed work environment?

As a Remote Knowledge Graph Software Engineer, collaboration often happens through virtual meetings, code repositories, and shared documentation platforms. You’ll regularly interact with data scientists, product managers, and other engineers to design and implement scalable graph-based solutions. Clear communication and proactive sharing of updates are essential, as team members may be spread across multiple time zones. Utilizing tools like Slack, Jira, and GitHub, remote engineers ensure alignment on project goals, resolve blockers quickly, and contribute to a cohesive team culture.

What is a Remote Knowledge Graph Software Engineer?

A Remote Knowledge Graph Software Engineer is a software developer who specializes in designing, building, and maintaining knowledge graph systems while working from a remote location. Knowledge graphs are structured representations of data that help in connecting and analyzing information through relationships and semantics. These engineers use technologies like RDF, SPARQL, and graph databases to enable advanced data querying and integration. They often collaborate with data scientists, analysts, and other engineers to solve complex data challenges across various industries. Working remotely allows them to contribute from anywhere, using communication and collaboration tools to stay connected with their teams.
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What cities are hiring for Remote Knowledge Graph Software Engineer jobs? Cities with the most Remote Knowledge Graph Software Engineer job openings:
What are the most commonly searched types of Knowledge Graph Software Engineer jobs? The most popular types of Knowledge Graph Software Engineer jobs are:
What states have the most Remote Knowledge Graph Software Engineer jobs? States with the most job openings for Remote Knowledge Graph Software Engineer jobs include:
What job categories do people searching Remote Knowledge Graph Software Engineer jobs look for? The top searched job categories for Remote Knowledge Graph Software Engineer jobs are:
Infographic showing various Remote Knowledge Graph Software Engineer job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
Ontology / Knowledge Engineer - Chase Semantic Layer

Ontology / Knowledge Engineer - Chase Semantic Layer

JP Morgan Chase

Jersey City, NJ • Remote

Full-time

Medical, Retirement

Re-posted 15 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 491 frontline employees who took The Breakroom Quiz

58th of 149 rated banks


Job description

As an Ontology and Knowledge Graph Engineer in Chase's Data and Analytics Office, you will curate the semantic data assets that connect our enterprise data estate to a shared, intelligent knowledge graph. You will work at the intersection of formal knowledge representation, logical data modeling, and data integration, building the ontologies and mapping assets that make our data semantically interoperable across use cases. Our team values precision, intellectual curiosity, and a deep commitment to making data meaningful - and you will find that culture reflected in everything we build together. This role offers an opportunity to contribute to a foundational capability that underpins enterprise AI, analytics, and data governance at one of the world's most influential financial institutions. 

Job Responsibilities 

  • Author Logical Data Model Ontologies that compose concepts from Upper Ontologies and Semantic Taxonomies to accurately represent how enterprise data is materialized across our data estate. 

  • Design and maintain Knowledge Graph Mapping assets that connect relational databases, REST APIs, in-memory data structures, and real-time streaming sources to a coherent enterprise knowledge graph. 

  • Curate Semantic Taxonomy structures using controlled vocabularies and Concept Schemes to organize enterprise concepts consistently across multiple business domains. 

  • Contribute to the design and governance of Upper Ontologies and Semantic Taxonomies that provide a shared, standardized conceptual backbone across enterprise semantic use cases.

  • Enable Virtual Knowledge Graph capabilities by ensuring mapping assets and ontology definitions support on-the-fly knowledge graph materialization without physical data movement. 

  • Engage with data architects, domain subject matter experts, AI engineers, and machine learning engineers to align ontology and mapping design decisions with both physical data structures and downstream Reasoning and Semantic Validation requirements. 

  • Participate in ontology governance activities including versioning, change management, deprecation policies, and cross-domain alignment reviews.

  • Translate complex business and data requirements into formal semantic representations that are technically rigorous and accessible to non-technical stakeholders.

Required Qualifications, Capabilities, and Skills 

  • 1 year of experience working with semantic web technologies, knowledge graph engineering, ontology development, or linked data systems in a professional or research setting .

  • Demonstrated understanding of formal knowledge representation principles, including class hierarchies, property definitions, and logical constraints. 

  • Familiarity with data mapping concepts that connect structured and semi-structured data sources to ontology-defined target vocabularies. 

  • Working knowledge of semantic data model layers, including foundational data models, schema definition languages, and controlled vocabulary organization standards.

  • Exposure to relational databases and semi-structured data sources, including REST APIs, in-memory structures, and streaming data pipelines. 

  • Ability to translate business and data requirements into formal semantic models in collaboration with data architects, domain experts, and engineering teams.

  • Awareness of Virtual Knowledge Graph concepts and the principles of connecting heterogeneous data sources to a shared semantic layer without physical data movement.

Preferred Qualifications, Capabilities, and Skills 

  • Hands-on experience authoring ontologies and knowledge graph mapping assets in a production enterprise environment.

  • Experience contributing to enterprise-scale knowledge graph programs within a large, complex organization. 

  • Familiarity with Reasoning and Semantic Validation frameworks used to enforce syntactic and semantic correctness of ontology-defined concepts.

  • Exposure to Upper Ontology design patterns and their role in standardizing conceptual overlaps across multiple enterprise use cases. 

  • Experience communicating complex semantic modeling decisions to non-technical stakeholders, including business analysts and product owners.

  • Familiarity with real-time data streaming platforms and their integration into knowledge graph mapping pipelines.

  • Experience contributing to ontology governance programs, including versioning strategies and cross-domain alignment reviews.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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