Red Team Engineer, Safeguards

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About The Role

Anthropic's Safeguards team is seeking a Red Team Engineer to help ensure the safety of our deployed AI systems and products. In this role, you'll take an adversarial approach to uncover vulnerabilities across our product ecosystem before they can be exploited by malicious actors. Your work will span from technical infrastructure vulnerabilities on our products to emergent risks from advanced AI capabilities.

While you'll bring best practices from traditional security approaches, the focus is on broader safety implications and novel abuse unique to advanced AI systems and associated products. You'll investigate the full spectrum of potential abuse — from coordinated account manipulation and payment fraud to novel exploitation of product features — and simulate sophisticated threat actors who chain multiple attack vectors to achieve their objectives.

Key Responsibilities

Conduct comprehensive adversarial testing across Anthropic's product surfaces, developing creative attack scenarios that combine multiple exploitation techniques Research and implement novel testing approaches for emerging capabilities, including agent systems, tool use, and new interaction paradigms Design and execute "full kill chain" attacks that emulate real-world threat actors attempting to achieve specific malicious objectives Build and maintain systematic testing methodologies that evaluate every aspect of our systems Develop automated testing frameworks to enable continuous assessment at scale Collaborate with Product, Engineering, and Policy teams to translate findings into concrete improvements Help establish metrics for measuring detection effectiveness of novel abuse

Minimum Qualifications

Experience in penetration testing, red teaming, or application security Experience in model jailbreaking and testing large-scale agentic workflows for non-obvious prompt injection vectors Strong technical skills in web application security, including hands-on expertise with security testing tools (e.g., Burp Suite, Metasploit, custom scripting frameworks) Experience building custom automation, including LLM-specific testing frameworks A track record of discovering novel attack vectors and chaining vulnerabilities in creative ways A public body of work such as CVEs, blog posts, or disclosed bug bounty reports Strong written and verbal communication skills, with the ability to explain technical concepts to varied audiences

Preferred Qualifications

Experience with AI/ML security or adversarial machine learning Understanding of AI safety considerations beyond traditional security, including modern guardrails against jailbreaks Experience testing API security and rate-limiting systems Background in testing business logic vulnerabilities and authorization bypass techniques Background in anti-fraud, trust & safety, or abuse prevention systems Familiarity with distributed systems and infrastructure security Familiarity with abuse detection mechanisms and the ability to engineer novel bypasses Adaptability to understand and build engagements around emerging threats outside your direct area of expertise The annual

Compensation

range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.