Offensive Cybersecurity Engineers: Build RL Environments for AI Evaluation
Its $150/hr is above the $55/hr median of the Agentic Tasks & RL Environments roles open now, whose typical pay runs $50–$120/hr. How that pay moves week by week is in our research on Agentic Tasks & RL Environments work.
Half of all Agentic Tasks & RL Environments roles come down within 13.3 days of being listed, and 42.8% are still up after four weeks. This one was posted today.
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About the role
What We're Researching
We're hiring offensive cybersecurity experts for a long-term paid project focused on AI evaluation. Our goal is to build and harden reinforcement learning environments that test the limits of frontier AI models. This work directly contributes to understanding and mitigating advanced security risks in emerging technologies.
How It Works
You will work remotely on an hourly basis to design and implement complex cybersecurity benchmarks. Your tasks will involve creating robust reinforcement learning environments tailored for offensive security scenarios. You will continuously harden these environments to ensure they provide rigorous evaluations for AI systems. The project requires ongoing collaboration and iterative development to keep pace with new vulnerabilities.
Who This Is For
We welcome offensive cybersecurity engineers, penetration testers, and security researchers with strong technical backgrounds. Ideal candidates have hands-on experience building secure environments or developing security benchmarks. Familiarity with reinforcement learning or AI evaluation frameworks is highly valued but not strictly required.
What You'll Do
- Design and build offensive cybersecurity reinforcement learning environments
- Harden existing benchmarks to withstand advanced AI interactions
- Develop rigorous evaluation criteria for frontier AI models
- Collaborate on a long-term hourly basis to iterate on security scenarios
Who Should Apply
- Professional experience in offensive cybersecurity or penetration testing
- Strong background in building or hardening technical environments
- Comfortable working on long-term hourly remote projects
- Interest in AI safety and model evaluation
Compensation
$150 per hour
About Terac
Terac is building the world's largest pool of vetted human experts for AI. Researchers, AI labs, and product teams use Terac to recruit, screen, and pay study participants across industries, languages, and skill sets.
Learn more at terac.com or on YouTube at @jointerac .
Where you can work
This role is 100% remote, for applicants located in United States.
From Terac's job posting, checked 9 Nov 2026.
The application
Just your details.
From Terac's apply page, checked 9 Nov 2026.
About Terac
Browse live AI-training and paid-study listings, each with pay shown upfront.
How it pays: Terac wallet, cashed out through its payout partner, which its safety page names as Whop: $12.50 minimum, up to $10,000 a day; in the few countries the partner cannot pay, through Virtual Incentives (its payment docs, read 8 Nov 2026).
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