Description
As a GenAI CBRNE Cyber Red Team Expert, you will play a critical role in adversarially testing and strengthening the safety guardrails of GenAI systems against high-risk cyber threats involving CBRNE domains.
You will combine deep cybersecurity expertise with CBRNE domain knowledge and hands-on AI red-teaming to design sophisticated adversarial prompts, multi-turn attack scenarios, jailbreaks, and model evaluations. Your work will identify circumstances in which GenAI systems could inadvertently provide information or capabilities that materially enable cyber-enabled CBRNE threats.
The role requires an adversarial mindset: thinking creatively about how malicious actors could manipulate AI systems, combine seemingly benign information across multiple interactions, circumvent safeguards, or exploit model behavior to obtain sensitive cyber-CBRNE information.
- Key Responsibilities
- Execute rigorous adversarial red-teaming of Generative AI models across cyber-CBRNE threat scenarios, systematically probing models for vulnerabilities, safeguard bypasses, dangerous capability escalation, and unintended disclosure of sensitive operational information.
- Design and execute adversarial prompts, jailbreaks, prompt mutations, multi-turn conversations, and scenario-based evaluations that test whether model safeguards remain effective against sophisticated or obfuscated cyber-CBRNE requests.
- Develop realistic cyber-CBRNE attack scenarios involving critical infrastructure, industrial control systems, operational technology, cyber-physical systems, laboratory environments, hazardous-material facilities, and other high-consequence systems.
- Evaluate whether models can be manipulated into materially assisting threat actors through attack planning, vulnerability analysis, target-specific reasoning, operational troubleshooting, or the aggregation of individually benign information into higher-risk workflows.
- Identify and document failure modes and attack patterns, including indirect requests, role-playing, encoded or obfuscated prompts, terminology substitution, decomposition of harmful objectives into benign-looking subtasks, and multi-turn escalation.
- Conduct systematic taxonomy audits and safety evaluations, classify model failures by severity and exploitability, reproduce findings, and provide actionable recommendations to AI safety and model-alignment teams.
- Develop repeatable red-team test suites, adversarial datasets, evaluation rubrics, and risk taxonomies for measuring model resilience against emerging cyber-CBRNE threats.
- Maintain current knowledge of emerging GenAI attack techniques, AI safety research, cyber threat intelligence, CBRNE security risks, and cybersecurity threats affecting critical infrastructure and high-consequence environments.
Requirements
Requirements
- Location: Must be located in and authorized to work within the United States (excluding Illinois and Texas) or United Kingdom.
- Education: Advanced degree in Cybersecurity, Computer Science, Engineering, Security Studies, CBRNE-related sciences, or a closely related technical field. Equivalent advanced professional, military, intelligence, government, or industry experience may be considered.
- Cybersecurity Expertise: Deep understanding of cybersecurity concepts, adversarial techniques, vulnerability analysis, attack chains, threat modeling, and defensive security.
- CBRNE Knowledge: Strong understanding of security and risk considerations associated with Chemical, Biological, Radiological, Nuclear, and/or Explosive environments, particularly their intersection with cyber and digital systems.
- Red Team Expertise: Demonstrated experience with red teaming, penetration testing, adversarial simulation, vulnerability research, security testing, threat emulation, or comparable offensive-security methodologies.
- GenAI Red Teaming: Experience or demonstrated aptitude in adversarial prompt generation, jailbreak research, prompt mutation, multi-turn testing, model behavior analysis, and evaluation of LLM safety controls.
- ICS/OT Knowledge: Familiarity with industrial control systems, SCADA, operational technology, cyber-physical systems, or critical-infrastructure environments.
- Adversarial Mindset: Ability to think creatively about how sophisticated users could circumvent model safeguards through decomposition, obfuscation, contextual manipulation, multi-turn interactions, or combinations of otherwise permissible information.
- Communication: Strong technical writing skills with the ability to clearly document prompts, attack methodology, model responses, vulnerabilities, reproduction steps, severity assessments, and recommended mitigations.
Preferred Qualifications
- Hands-on experience with LLM red teaming, AI safety evaluations, jailbreak research, prompt engineering, adversarial prompt writing, or model vulnerability research.
- Experience developing red-team test cases, adversarial datasets, model evaluation benchmarks, attack taxonomies, or automated LLM evaluation pipelines.
- Familiarity with frontier AI safety concepts, dangerous-capability evaluations, responsible scaling frameworks, model safeguards, and emerging GenAI security standards.
- Professional experience in offensive security, penetration testing, vulnerability research, cyber threat intelligence, incident response, or adversary emulation.
- Familiarity with MITRE ATT&CK, MITRE ATT&CK for ICS, NIST cybersecurity frameworks, IEC 62443, and other critical-infrastructure cybersecurity standards.
- Experience working in national security, defense, intelligence, government laboratories, critical infrastructure, CBRNE security, or high-consequence industrial environments.
- Relevant offensive-security, ICS/OT security, or cybersecurity certifications are advantageous.
- Expertise in one or more of the following red-team areas:
- GenAI Cyber Red Teaming: Adversarial testing of LLMs for cyber capabilities, including attempts to circumvent safeguards through prompt manipulation, decomposition, multi-turn interactions, and other adversarial techniques.
- ICS/OT Red Teaming: Security assessment and adversarial testing involving industrial control systems, SCADA, operational technology, cyber-physical systems, and critical infrastructure.
- Chemical & Industrial Cyber Risk: Understanding of cyber threats affecting chemical facilities, hazardous-material environments, industrial processes, process-control environments, and associated safety systems.
- Biological & Laboratory Cyber Risk: Understanding of cyber and information-security risks affecting laboratories, biotechnology environments, research infrastructure, laboratory automation, and associated digital systems.
- Radiological & Nuclear Cyber Risk: Understanding of cybersecurity risks and safeguards associated with nuclear or radiological facilities, monitoring systems, control environments, and supporting infrastructure.
- Cyber-Physical & High-Consequence Threats: Expertise in analyzing scenarios where compromise of digital systems could produce significant physical, safety, environmental, or CBRNE consequences.
The salary range for this role is $150K - $178K OTE - Range may vary based on experience. Salary at the time of offer will be commensurate with experience.
Advanced degree or equivalent experience; deep cybersecurity and CBRNE expertise; red teaming and GenAI testing experience; ICS/OT knowledge; strong technical writing; US or UK work authorization.
Key Responsibilities
- executing red-teaming
- designing attack scenarios
- documenting vulnerabilities
Skills & Tools
Generative AI, Large Language Models (LLM), SCADA, MITRE ATT&CK, MITRE ATT&CK for ICS, NIST, IEC 62443
Job Details
- Category: Information Technology
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — United Kingdom or United States
- Salary: USD 150,000 – 178,000 / year
- Languages: English
About Alice
A trust, safety, and security company protecting AI-enabled communication technologies across the AI lifecycle. — Industry: Information Technology