Technical CBRN-E Threat Investigator
AnthropicRemote-Friendly (Travel-Required) | San Francisco, CA | Washington, DCPosted 24 February 2026
Tech Stack
Job Description
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
We are looking for a Technical CBRN-E Threat Investigator to join our Threat Intelligence team. In this role, you will be responsible for detecting, investigating, and disrupting the misuse of Anthropic's AI systems for Chemical, Biological, Radiological, Nuclear, and Explosives (CBRN-E) threats. We are particularly interested in candidates with deep expertise in either chemical defense or biodefense.
You will work at the intersection of AI safety and CBRN security, conducting thorough investigations into potential misuse cases, developing novel detection techniques, and building robust defenses against threat actors who may attempt to leverage our AI technology for developing weapons, synthesizing dangerous compounds, or creating biological harm. Your specialized domain expertise will be critical to protecting against some of the most serious potential misuses of AI systems.
Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays.
Responsibilities
Detect and investigate attempts to misuse Anthropic's AI systems for developing, enhancing, or disseminating CBRN-E weapons, pathogens, toxins, or other threats to harm people, critical infrastructure, or the environment
Conduct technical investigations using SQL, Python, and other tools to analyze large datasets, trace user behavior patterns, and uncover sophisticated CBRN-E threat actors
Develop CBRN-E-specific detection capabilities, including abuse signals, tracking strategies, and detection methodologies tailored to dual-use research concerns
Create actionable intelligence reports on CBRN-E attack vectors, vulnerabilities, and threat actor TTPs leveraging AI systems
Conduct cross-platform threat analysis grounded in real threat actor behavior, open-source research, and publicly reported programs
Collaborate with policy and enforcement teams to make informed decisions about user violations and ensure appropriate mitigation actions
Engage with external stakeholders including government agencies, regulatory bodies, scientific organizations, and biosecurity/chemical security research communities
Inform safety-by-design strategies by forecasting how threat actors may leverage advances in AI technology for CBRN-E purposes
You may be a good fit if you
Have deep domain expertise in biosecurity, chemical defense, biological weapons non-proliferation, dual-use research of concern (DURC), synthetic biology, or related CBRN-E threat domains
Have demonstrated proficiency in SQL and Python for data analysis and threat detection
Have experience with threat actor profiling and utilizing threat intelligence frameworks
Have hands-on experience with large language models and understanding of how AI technology could be misused for CBRN-E threats
Have excellent stakeholder management skills and ability to work with diverse teams including researchers, policy experts, legal teams, and external partners
Can present analytical work to both technical and non-technical audiences, including government stakeholders and senior leadership
Strong candidates may also have
Advanced degree (MS or PhD) in biological sciences, chemistry, biodefense, biosecurity, or related field
Real-world experience countering weapons of mass destruction or other high-risk asymmetric threats
Experience working with government agencies or in regulated environments dealing with sensitive CBRN-E information
Background in AI safety, machine learning security, or te ... (truncated, view full listing at source)
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