AI Security Red Teamer: Offensive AI Risk & Defense

Dorado; Seattle (WA); On-site; USD 160,000 - 260,000; Full time

Job summary

Handshake is seeking a Cybersecurity Red Teamer to evaluate AI model safety against malware, exploit tooling, and attack guidance. You will craft adversarial prompts, assess model outputs for exploitability, and test across kill-chain stages from reconnaissance to exfiltration.

Deep cybersecurity expertise and experience with multiple LLMs are essential. You will collaborate with AI researchers and policy teams to improve evaluation frameworks and stay current with TTPs and CVEs in a

Qualifications

• Professional experience in offensive security, penetration testing, red teaming, vulnerability research, malware analysis, threat intelligence, or incident response.
• Ability to read, write, and evaluate code across common languages used in offensive tooling (Python, PowerShell, Bash, C/C++, JavaScript, or similar).
• Understanding of common attack frameworks, techniques, and procedures (MITRE ATT&CK, OWASP, etc.).
• Ability to assess the functional correctness and real-world exploitability of model-generated technical output.
• Strong hands-on experience using multiple LLMs (ChatGPT, Claude, Gemini, open-source models, etc.).
• Creative, adversarial problem-solving skills.
• Clear and precise written communication, including the ability to explain technical risk to non-specialist audiences.
• Strong ethical judgment and the ability to separate adversarial thinking from personal values.
• Self-directed, collaborative, and comfortable in feedback-heavy environments.

Responsibilities

• Design technically grounded adversarial prompts that test whether models provide meaningful uplift across the cyber kill chain (reconnaissance through exfiltration and impact).
• Evaluate model-generated code and technical output for functional correctness, assessing whether outputs represent real exploits, plausible attack tooling, or non-functional noise.
• Test model behavior across offensive categories including malware generation, vulnerability exploitation, social engineering content, credential harvesting, privilege escalation, C2 infrastructure setup, and data exfiltration techniques.
• Probe dual-use boundaries, testing how models handle queries that blend legitimate security research, penetration testing, and defensive operations with offensive applications.
• Simulate attacker personas at varying skill levels (opportunistic, intermediate, advanced/APT) to assess how model risk scales with user sophistication.
• Test multi-step and multi-turn attack chains, including scenarios where early turns establish benign context before pivoting to malicious requests.
• Score model responses against structured harm taxonomies and severity rubrics calibrated to real-world exploitability.
• Document findings with clear technical reasoning, including what a response gets right, what it gets wrong, and what level of attacker it would realistically assist.
• Contribute to the development and refinement of cybersecurity-specific evaluation frameworks and threat models.
• Collaborate with other red teamers, AI researchers, and policy teams to translate findings into actionable model improvements.
• Stay current on evolving TTPs, CVEs, jailbreak techniques, and the intersection of AI and offensive security.

Skills

Offensive security

Code review (Python/PowerShell/Bash/C/

Education

Security certifications (OSCP/OSCE/GPEN/GXPN/CEH)

Job description

Handshake is seeking a Cybersecurity Red Teamer to evaluate AI model safety against malware, exploit tooling, and attack guidance. You will craft adversarial prompts, assess model outputs for exploitability, and test across kill-chain stages from reconnaissance to exfiltration.

Deep cybersecurity expertise and experience with multiple LLMs are essential. You will collaborate with AI researchers and policy teams to improve evaluation frameworks and stay current with TTPs and CVEs in a