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Open nowPosted 92 days ago

AI Red Team Engineer

White Circle22 open roles

Where
Global
Work mode
Remote
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Your applicationOpen nowAI Red Team EngineerWhite Circle · Global

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. White Circle postings stay open a median of 6 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.2%30 days
This job: posted 92 days ago

White Circle median: 6 days open

The posting

TL;DR: We're looking for an AI Red Team Engineer to break LLM-powered systems responsibly, automate repetitive attacks, and turn their findings into clear evidence that powers customer demos, security reviews, and sales conversations. You'll own hands-on adversarial testing end to end: find the failure, prove it, script it, and write it up.

About us

White Circle https://whitecircle.ai/ is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale.

- We’ve recently raised our Series A funding round, taking our total funding to $70M. Our investors include top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others

- We process over one hundred million API calls every month

- We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model

We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need.

What you’ll do

- Red-team LLM-powered systems: chatbots, copilots, RAG pipelines, AI agents, tool-calling workflows, and API-based AI products.

- Test for jailbreaks, prompt injection, system-prompt and tool leakage, sensitive-data and context leakage, unsafe outputs, policy bypass, tool misuse, excessive agency, resource and token-cost abuse, and business-logic abuse.

- Write lightweight Python to automate attacks, run prompt sets, call model APIs, collect and score responses, and generate repeatable reports.

- Build and maintain an internal attack library: prompts, scenarios, test cases, regression tests, scoring rubrics, and reusable demo cases.

- Turn model failures into clear reports: what happened, why it matters, how to reproduce it, how severe it is, and how to fix it.

- Convert successful attacks into regression tests and product requirements.

- Track new red-team and safety techniques and fold the useful ones into our tests.

- Support GTM by producing strong, credible evidence for customer demos, security reviews, and sales conversations.

You'll fit right in if you

- Genuinely love breaking things and reasoning adversarially.

- Have a background in QA automation, AppSec, API/security/pen testing, or bug bounty.

- Have strong Python scripting skills.

- Have experience testing APIs, web apps, backends, or SaaS products.

- Are hands-on with LLMs, prompts, system instructions, RAG, agents, and tool/function calling.

- Understand LLM-specific abuse vectors (prompt injection, jailbreaks, data leakage, tool misuse, excessive agency, token-cost exhaustion).

- Can find bypasses, abuse edge cases, chain failures, and reason about real-world impact.

- Can separate real customer risk from low-impact prompt tricks.

- Write clear, reproducible bug reports in clear English.

- Can move fast without perfect requirements.

- Hold a firm ethical line: you red-team to make systems safer, operate within scope and the law, and don't produce or traffic in genuinely harmful material.

A big plus

- Experience with Burp Suite, Postman, Playwright, pytest.

- Experience with modern LLM red-teaming automated agents and pipelines.

- Familiarity with LangChain, LangGraph, LlamaIndex, RAG pipelines, AI agents, tool/function calling, and LLM-as-judge evaluation.

- Familiarity with OWASP LLM Top 10, OWASP Web Top 10, MITRE ATLAS, or other AI security taxonomies.

- Experience testing RAG systems, AI agents, tool-calling workflows, browser agents, or internal copilots.

- Experience writing customer-facing security reports.

- Experience with trust & safety, abuse prevention, fraud, moderation, or platform security.

- Experience building eval pipelines, regression suites, dashboards, or CI-friendly security tests.

- A track record in CTFs, red-team competitions, or responsible-disclosure / bounty programs.

Compensation & benefits

- Competitive compensation package, including equity

- Flexible Time Off

- Language lessons to help you improve your English or French

- Learning and development support for courses, conferences, and opportunities to grow your skills

- All the hardware, subscriptions, tools, and services you need

- Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella

Process

1. Intro call with Talent Team

2. Test assignment

3. Technical interview

4. Final call with CEO

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