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Part Time Remote Ai Prompt Engineer information

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$30.5K

$68.6K

$115.5K

How much do part time remote ai prompt engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for part time remote ai prompt engineer in the United States is $68,617.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $74,500.00 per year, depending on experience, location, and employer.

What is the difference between Part Time Remote Ai Prompt Engineer vs Part Time Remote Data Annotator?

AspectPart Time Remote Ai Prompt EngineerPart Time Remote Data Annotator
Required CredentialsBasic understanding of AI, NLP, and prompt engineeringAttention to detail, basic technical skills
Work EnvironmentRemote, flexible hours, focused on AI and NLP projectsRemote, flexible hours, focused on data labeling tasks
Employer & Industry UsageTech companies, AI startups, research labsData companies, AI training firms, machine learning teams
Search & Comparison IntentUnderstanding AI prompt roles, job differencesClarifying data annotation roles, job scope

The Part Time Remote Ai Prompt Engineer focuses on designing and refining prompts for AI models, requiring knowledge of NLP and AI concepts. In contrast, the Part Time Remote Data Annotator primarily labels data to train AI systems, emphasizing attention to detail. Both roles are remote and part-time, but they serve different functions within AI development teams.

More about Part Time Remote Ai Prompt Engineer jobs
What cities are hiring for Part Time Remote Ai Prompt Engineer jobs? Cities with the most Part Time Remote Ai Prompt Engineer job openings:
What are the most commonly searched types of Remote Ai Prompt Engineer jobs? The most popular types of Remote Ai Prompt Engineer jobs are:
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Part Time Remote Ai Prompt Engineer jobs near you
Infographic showing various Part Time Remote Ai Prompt Engineer job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $68,617 per year, or $33 per hour.
AI Safety Engineer (Red Teaming) - Remote

AI Safety Engineer (Red Teaming) - Remote

micro1 AI

Seattle, WA • Remote

$50 - $90/hr

Part-time

Posted 11 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.

Apply