About the job
Come build and lead Gray Swan's cyber safety capability from the ground up, serving as the technical authority on AI-enabled cyber risk across red-teaming, evaluation, benchmarking, defenses, and safety infrastructure development. You'll help define how frontier AI systems are evaluated for offensive cyber capabilities while partnering with leading AI labs to reduce real-world security risks.
This role sits at the intersection of offensive security, AI safety, and machine learning. You'll transform deep cybersecurity expertise into scalable evaluation methodologies, safety infrastructure, and automated defenses that help establish industry standards for frontier model security.
Responsibilities
- Design and lead adversarial evaluations of frontier LLMs for offensive cyber capabilities, including vulnerability discovery, exploit development, malware generation, privilege escalation, social engineering, persistence, and autonomous cyber operations across text, agentic, and multimodal systems.
- Partner closely with machine learning engineers to translate cybersecurity expertise into scalable benchmarks, classifiers, guardrails, automated detection systems, and evaluation infrastructure for both internal products and frontier AI lab deployments.
- Develop and maintain Gray Swan’s catastrophic cyber harm taxonomy, continuously evolving cyber evaluation frameworks as frontier model capabilities rapidly advance.
- Produce technical risk assessments and actionable recommendations for frontier AI labs, enterprise customers, and internal stakeholders, helping guide responsible model deployment and security mitigations.
- Build, mentor, and lead a world-class team of cybersecurity subject matter experts while establishing scalable evaluation processes, quality standards, and technical infrastructure.
- Represent Gray Swan as the company's cybersecurity authority, collaborating with frontier AI labs, security researchers, government partners, and the broader AI safety and cybersecurity communities.
Qualifications
Minimum
- Deep technical expertise in offensive cybersecurity, vulnerability research, exploit development, penetration testing, malware analysis, reverse engineering, or a closely related field through industry, research, or equivalent experience.
- Significant experience assessing advanced cyber threats, offensive tooling, or AI-enabled cyber capabilities, especially in critical infrastructure domains.
- Hands-on experience conducting adversarial evaluations, AI red-teaming, LLM security research, or building evaluation datasets for frontier AI systems.
- Comfortable operating at the intersection of cybersecurity research, AI safety, and machine learning engineering.
- Thrive in highly ambiguous, fast-moving environments where you'll define strategy while building entirely new capabilities.
- A builder who enjoys creating teams, infrastructure, and evaluation systems from scratch.
Preferred
- Experience developing machine learning models, AI security classifiers, or automated cyber detection systems.
- Hands-on experience red-teaming frontier language models, jailbreaking, prompt injection research, or agentic AI evaluations.
- Experience working with frontier AI labs, national security organizations, or leading cybersecurity research teams.
- Background in threat intelligence, autonomous cyber operations, AI agent security, or AI governance.
- Strong software engineering experience in Python, Go, Rust, or other systems programming languages.