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OpenTrain

Cybersecurity Specialist (AI Safety)

You will build complete, sandboxed evaluation tasks for AI agents. Each task includes an instruction for the agent, a containerized target system, a hidden deterministic verifier that checks the result, and a reference solution.

Field
Cybersecurity
Where
Remote
Commitment
part time
Hours
up to 20/week
Posted
7 days ago

How this pay compares

Among platforms with 10 or more priced cybersecurity roles, OpenTrain AI has the highest median ($93/hr across 14 roles) and Alignerr the lowest ($50/hr across 33).

OpenTrain AI roles that closed since late October stayed listed a median of 31 days (122 roles). OpenTrain AI posted this one 7 days ago.

Computed from 2,746 open roles we track across Mercor, micro1, Handshake AI, Alignerr, Appen and OpenTrain AI, refreshed daily. Midpoints of listed ranges; “up to” ceilings are left out of medians.

Open cybersecurity roles on each platform

The same kind of work, priced on every platform we track, with the best-paid open role on each.

All 58 open cybersecurity roles →

The full listing

As posted on OpenTrain AI. See the original

The work

You will build complete, sandboxed evaluation tasks for AI agents. Each task includes an instruction for the agent, a containerized target system, a hidden deterministic verifier that checks the result, and a reference solution.

The work focuses on AI red teaming rather than traditional vulnerability assessment and penetration testing. You will test how agents respond to prompt injection, jailbreaks, tool-call abuse, unsafe autonomous actions, scope escape, and reward hacking.

  • Author security scenarios and agent-facing instructions from scratch.
  • Build Dockerized target environments and write oracle solutions.
  • Create deterministic verifiers for checking agent behavior.
  • Judge multi-step agent trajectories and identify unsafe or out-of-scope actions.
  • Test prompt injection, jailbreaks, tool misuse, and reward-hacking risks.

What it pays and takes

This is a remote freelance contractor engagement for part-time work. The role is open worldwide and is intended for contributors with intermediate experience in AI safety evaluation or related red-team work.

  • Pay: $300 per accepted task, paid after quality control.
  • Time: Less than 20 hours per week.
  • Location: Remote and open worldwide.
  • Experience: Hands-on LLM or AI-agent red teaming, jailbreak or prompt-injection research, or AI safety evaluation.
  • Technical skills: Docker, Git, and Python.
  • Required ability: Write deterministic verifiers and evaluate multi-step agent trajectories.
  • Useful background: Published red-team reports, adversarial machine-learning research, or reinforcement-learning environment experience.

How it works

Apply on OpenTrain. The employer reviews applications there.

  • Selection includes a short take-home assignment and one feedback round.

About AI training work

AI training is the human work used to build and evaluate artificial intelligence, including testing model responses and reviewing how agents behave. People with security and technical expertise are needed to find failure modes and help make AI systems safer.

From applying to your first payment on OpenTrain AI

  1. 1

    Create a profile

    Create a free OpenTrain profile with your domains, languages and hourly rate.

  2. 2

    Apply

    Apply to the listing. Some listings hire through OpenTrain; others send you to the hiring platform.

  3. 3

    Funded milestones

    The client funds each milestone before work starts.

  4. 4

    First payment

    OpenTrain pays out to your connected payout method when the client approves the milestone. It doesn't publish a fixed payout schedule.

Sources: OpenTrain: AI training careers, OpenTrain docs: invoicing and payouts

Full OpenTrain AI profile: watch-outs and the public record →

Pay history

OpenTrain AI has listed this role at $300 per task since Nov 4, 2026 with no change.

What workers report about OpenTrain AI

Anonymous reports from people who applied or worked there: whether they got work, what they were paid and how fast.

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