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Part Time Ai Chatbot Prompt Engineer & Writer Jobs

Uare.ai

AI / Video Engineer

Los Altos, CA · On-site

Working part-time with flexible hours, you'll experiment with the latest AI video generation tools ... Deep understanding of prompt engineering and creative direction with AI tools * Portfolio ...

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Part Time Ai Chatbot Prompt Engineer Writer information

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$157K

$190K

$220K

How much do part time ai chatbot prompt engineer & writer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for part time ai chatbot prompt engineer & writer in the United States is $190,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $173,500.00 and $206,500.00 per year, depending on experience, location, and employer.

What is the difference between Part Time Ai Chatbot Prompt Engineer & Writer & vs Part Time Ai Content Writer?

AspectPart Time Ai Chatbot Prompt Engineer & WriterPart Time Ai Content Writer
Required SkillsPrompt engineering, AI interaction, writingContent creation, SEO, copywriting
Work EnvironmentRemote, tech-focusedRemote or on-site, marketing or media firms
Industry UsageAI development, chatbot designDigital marketing, blogging, media

While both roles involve writing, the Prompt Engineer & Writer focuses on designing prompts for AI chatbots, requiring technical understanding of AI interactions. The Content Writer creates general content for marketing or media, emphasizing SEO and audience engagement. Both roles often work remotely and are in tech-driven industries, but their core tasks and skill sets differ significantly.

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Part Time Ai Chatbot Prompt Engineer Writer jobs near you
AI Safety Engineer (Red Teaming) - Remote

AI Safety Engineer (Red Teaming) - Remote

micro1 AI

San Antonio, TX • Remote

$50 - $90/hr

Part-time

Posted 13 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