Staff Attack Engineer, AI/LLM

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, c...

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.

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Duties, responsibilities, and activities may change at any time with or without notice. 

Expert-level Python and software engineering skills.
Solid penetration testing fundamentals and understanding of common attack chains.
Familiarity with AI/LLM security frameworks (e.g., OWASP Top 10 for LLMs, MITRE ATLAS).
Experience in a security product or offensive security team, ideally with shipped offensive capabilities or tooling.
Proven ability to break AI/LLM and agentic systems.
Clear understanding of trust boundaries around AI tools, data sources, and permissions, and how to systematically test and exploit them.
Expert-level ownership – drives high-complexity, high-risk programs and sets strategy, not just execution.
Self-motivated – identifies problems and builds solutions proactively.
Industry obsessed – tracks the fast-moving AI security landscape and can speak to recent developments, new attacks, and where the field is heading.
Experience with other cloud AI services (e.g., Azure OpenAI, GCP Vertex AI).
Contributions to AI security research (blog posts, conference talks, CVEs, open-source tools).
Experience with AWS Bedrock and AWS Agent Core.
Familiarity with graph databases (e.g., Neo4j).
Background in traditional exploit development or vulnerability research.
CTF experience, particularly in AI/ML-focused challenge categories.