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Remote Knowledge Engineer Jobs in Colorado (NOW HIRING)

Maxar

Software Development Engineer

Westminster, CO · On-site +1

$82K - $109K/yr

Knowledge of geospatial, geodesic, photogrammetric, or remote sensing technologies. * Strong ... Collaborative and innovative engineering culture. * Exposure to modern software development ...

Leidos

Civil/Structural Engineer

Denver, CO · On-site +1

Fully remote would be considered on a case-by-case basis. There is an identical senior level ... Knowledge of Mathcad, AutoCAD, and other structural analysis software is a plus. * Ability to ...

Doowii, Inc

Data Engineer

Denver, CO · On-site +1

$117K - $141K/yr

Knowledge of LLM evaluation, vector stores, or semantic layers We're open to adjusting the role ... Remote-work environment Equal Opportunity Doowii is an Equal Opportunity Employer and values ...

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Remote Knowledge Engineer information

What are the key skills and qualifications needed to thrive as a Remote Knowledge Engineer, and why are they important?

To excel as a Remote Knowledge Engineer, you generally need expertise in knowledge management, ontologies, data modeling, and a relevant degree in computer science or information science. Familiarity with technical tools such as semantic web technologies (e.g., RDF, OWL), knowledge graph platforms, and query languages like SPARQL is often required. Strong analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating across distributed teams and translating complex information. These skills ensure the creation, organization, and optimization of knowledge systems that support informed decision-making and efficient remote operations.

What is the difference between Remote Knowledge Engineer vs Remote Data Scientist?

AspectRemote Knowledge EngineerRemote Data Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of ontologies and knowledge basesBachelor's or higher in CS, Statistics, or related; proficiency in programming and statistical analysis
Work EnvironmentCollaborates with AI teams, develops knowledge systems, often in tech or AI companiesAnalyzes data, builds models, works in tech, finance, or healthcare sectors
Employer & Industry UsageUsed in AI, knowledge management, and enterprise solutionsCommon in data-driven industries like tech, finance, healthcare

While both roles involve technical expertise, Remote Knowledge Engineers focus on developing and managing knowledge bases and AI systems, whereas Remote Data Scientists analyze data to derive insights. Both roles often work in tech industries and require strong technical backgrounds, but their core responsibilities differ significantly.

What is a Remote Knowledge Engineer?

A Remote Knowledge Engineer is a professional who designs, develops, and maintains systems that organize and manage knowledge, often using artificial intelligence and machine learning. They work from a remote location, leveraging digital tools to gather, structure, and analyze information for organizations. Their responsibilities may include building knowledge graphs, developing ontologies, and ensuring that data is accessible and usable for decision-making. Remote Knowledge Engineers collaborate with subject matter experts, software developers, and data scientists to optimize knowledge management solutions. They play a key role in helping organizations turn complex data into actionable insights, all while working outside of a traditional office environment.

How does a Remote Knowledge Engineer typically collaborate with subject matter experts and development teams?

As a Remote Knowledge Engineer, you will frequently interact with subject matter experts (SMEs) to extract, structure, and validate knowledge for use in AI systems or knowledge bases. Collaboration is often conducted through virtual meetings, shared documentation, and project management tools. You’ll also work closely with developers to integrate structured knowledge into systems and ensure accuracy. Effective communication and the ability to translate complex concepts into structured data formats are key to success in this remote, cross-functional environment.
What are popular job titles related to Remote Knowledge Engineer jobs in Colorado? For Remote Knowledge Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Knowledge Engineer jobs in Colorado look for? The top searched job categories for Remote Knowledge Engineer jobs in Colorado are:
What cities in Colorado are hiring for Remote Knowledge Engineer jobs? Cities in Colorado with the most Remote Knowledge Engineer job openings:
Remote Knowledge Engineer jobs near you
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Colorado Springs, CO • Remote

$50 - $90/hr

Part-time

Posted 10 days ago

Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert


Role Type: Contractor


Location: Remote


micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
  2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
  3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
  4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
  5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
  6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.


Preferred Qualifications

  1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
  2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
  3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
  4. High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations.
  5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
  6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
  7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.

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