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Remote Knowledge Graph Software Engineer Jobs in Tucson, AZ

Universal Avionics

AI-ML Engineer 1

Tucson, AZ · On-site +1

$110K - $132K/yr

Knowledge of basic algorithms (linear regression, decision trees, k-NN, etc.) and supervised ... Software Development * Understanding of software engineering best practices: version control (Git ...

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Remote Knowledge Graph Software Engineer information

See Tucson, AZ salary details

$60K

$139.5K

$194.3K

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

As of Jun 22, 2026, the average yearly pay for remote knowledge graph software engineer in Tucson, AZ is $139,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $163,600.00 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.
What are the most commonly searched types of Knowledge Graph Software Engineer jobs in Tucson, AZ? The most popular types of Knowledge Graph Software Engineer jobs in Tucson, AZ are:
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What job categories do people searching Remote Knowledge Graph Software Engineer jobs in Tucson, AZ look for? The top searched job categories for Remote Knowledge Graph Software Engineer jobs in Tucson, AZ are:
Remote Knowledge Graph Software Engineer jobs near you
Associate Software Engineer (Open3D) - Remote

Associate Software Engineer (Open3D) - Remote

micro1 AI

Tucson, AZ • Remote

$20 - $120/hr

Part-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Junior Software Engineer (Open 3D Engine)


Job Type: Contractor


Location: Remote


Job Summary: Join our client's team as a Junior Software Engineer (Open 3D Engine) and play a pivotal role in training next-generation AI systems for 3D environments. You will leverage your O3DE expertise, spanning the Component Entity System, Atom Renderer, and physics simulations, to generate high quality, synthetic data, enabling AI models to learn, reason, and construct high performance, AAA quality digital worlds.


Key Responsibilities:

  1. Design, develop, and implement interactive 3D scenes and simulations using Open 3D Engine (O3DE) for AI training purposes.
  2. Leverage the full suite of O3DE tools—including Atom Renderer, Component Entity System, Gems, and Asset Processor—to create high-fidelity, effective environments.
  3. Collaborate with the customer’s team to transform conceptual ideas into finished AI training workflows and simulations.
  4. Integrate Python and C++ scripts for enhanced functionality and automation within O3DE projects.
  5. Utilize AWS services to support robust, scalable 3D simulation deployment and asset management.
  6. Document processes and communicate progress clearly through strong written and verbal updates.
  7. Troubleshoot and optimize simulation performance, ensuring accuracy and efficiency for AI training objectives.


Required Skills and Qualifications:

  1. Hands-on experience with O3DE (Open 3D Engine), including a deep understanding of core tools and asset workflows.
  2. Proficiency in Python and C++ for 3D scene development and automation.
  3. Experience building interactive 3D environments from concept to completion, tailored for simulation and AI training.
  4. Familiarity with Atom Renderer, Component Entity System, Gems, and Asset Processor within O3DE.
  5. Strong written and verbal communication skills, with the ability to clearly document and present technical concepts.
  6. Basic knowledge of AWS infrastructure and its application for cloud-based development and deployment.
  7. Background in game development, simulation, or real-time graphics projects.


Preferred Qualifications:

  1. Previous experience working directly on AI training or simulation projects within O3DE.
  2. Exposure to asset management pipelines and collaborative development environments.
  3. Demonstrated initiative in adopting new O3DE tools and staying current with engine updates.

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