AI Red Team Engineer
Posted 1 Sep 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 2+ yrs
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
- Visa sponsorship
- Offered
No salary listed for this role.
THE OPPORTUNITY
We are currently building Watcher, a monitoring tool for coding agents. Our monitoring research agenda attempts to translate compute into safety at scale. Red-teaming previously sat inside the RS (Control) role as a partial responsibility. As it's grown from a single pilot into a recurring need, it now needs a dedicated owner.
As the AI Red Team Engineer, you will help build the practice of red-teaming AI monitors (both Watcher's own defenses and frontier labs' monitoring systems (see our pilot campaign red-teaming Anthropic's auto mode). You will hunt for attack surfaces monitors that haven't been tested against yet and turn what you find into fixes. You'll work closely with Marius (CEO & currently leads the monitoring efforts), control researchers and product engineers.
You will like this opportunity if you think like an attacker and want your adversarial findings to directly strengthen AI monitoring systems. You will join a small team and will have significant ability to shape the team & tech, and have the ability to earn responsibility quickly.
KEY RESPONSIBILITIES
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Design and run red-teaming campaigns combining severity-graded failure-mode injection into real trajectories, static monitoring benchmarks (e.g. MonitoringBench), and dynamic off-policy control red-teaming.
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Identify novel attack surfaces monitors haven't been tested against.
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Build and maintain automated red-teaming pipelines that attack monitors at scale, rather than relying on one-off manual probing.
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Design iterative adversarial red-team/blue-team games, working with RS (Control) on the blue-team side to keep escalating attack difficulty as monitors improve.
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Track the research literature and real-world incidents on agent failure modes, monitor evasion, and adversarial robustness.
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Turn each campaign into specific, actionable recommendations for monitor developers e.g. on time of intervention, user authorisation, trust boundaries, and monitor visibility
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Write up campaign findings as external publications and internal reports.
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Feed findings back into Watcher's monitor development and Apollo's blue-teaming research, so lessons learned externally harden our own product.
JOB REQUIREMENTS
Must-haves
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2+ years of experience in offensive security, adversarial ML, or red-teaming of AI systems.