Staff Attack Engineer, AI/LLM

🇺🇸 San Francisco, California
$2K - $3K Annual
Posted 4 weeks ago
Expires July 6, 2026

Get to Know Us

Horizon3.ai is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find and fix and verify exploitable attack vectors before criminals exploit them. Our flagship product, the NodeZeroTM platform, delivers production-safe autonomous pentests and other key assessment operations that scale across the largest internal, external, cloud, and hybrid cloud environments. NodeZero has been adopted by organizations of all sizes, from small educational institutions to government agencies and Global 100 enterprises. It is used by ITOps/SecOps teams, consulting pentesters, and MSSPs and MSPs. 

We are a fusion of former U.S. Special Operations cyber operators, startup engineers, and formerly frustrated cybersecurity practitioners. We're committed to helping solve our common security problems: ineffective security tools, false positives resulting in alert fatigue, blind spots, "checkbox” security culture, cybersecurity skills shortage, and the long lead time and expense of hiring outside consultants. Collectively, we are a team of learn it alls, committed to a culture of respect, collaboration, ownership, and results.

 

SUMMARY

We are hiring a Staff Attack Engineer specializing in AI/LLM security to join our team. You will break AI and agentic systems and turn that research into automated attacks inside NodeZero, our autonomous pentesting platform.

This is not consulting or manual pentesting; the goal is to build repeatable, scalable attack patterns that run autonomously across customer environments. You’ll also help drive our LLM-powered offensive capabilities and act as a technical leader for AI/LLM offense.

ESSENTIAL FUNCTIONS

ATTACKING AI/LLM SYSTEMS

- Break AI and agentic systems and translate that research into automated, repeatable attack modules for NodeZero.

- Design and execute prompt injection and defense evasion attacks, focusing on generalized, reusable patterns.

- Conduct too...

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