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.
Anthropic's Application Security team secures the systems that build, serve, and increasingly are Claude. The attack surface is unlike most AppSec work: multi-agent orchestration, sandboxed code execution, agents holding delegated credentials, untrusted tool output crossing trust boundaries — problems with little prior art and no off-the-shelf playbook.
The way the team works is also different. We use Claude as our primary tool across every part of the job: it drives our static analysis, drafts and fixes vulnerabilities as pull requests, performs first-line bug bounty triage, and assists threat modeling for design reviews. The human work is the judgment layer — system-level reasoning, deciding what matters, and building the next thing the model can't do yet.
This is a builder's role on a senior team. We hire engineers who ship production systems and clear a hands-on threat-modeling bar — people who can find the vulnerability but would rather build the system that finds them all. Every engineer owns a system end-to-end, and the team's work has shaped customer-facing product security — including Claude Code's security review tooling, its security guidance plugin, sandboxing, and auto mode.
- Design, build, and operate Claude-powered security systems — LLM-driven code analysis, automated vulnerability remediation, AI-assisted threat modeling — and own one or more of them end-to-end, including the cross-functional relationships that come with it
- Lead secure design reviews and threat modeling for novel AI systems, identifying risks that don't map to existing frameworks
- Evolve a public bug bounty program where automation handles routine triage and root-cause work, and engineers handle escalations and corner cases
- Partner with Product, Infrastructure, and Research teams as an embedded security owner — consulting on launches, shaping architecture, and influencing decisions where security is the constraint
- Share an operational on-run rotation with the rest of the team — bounty escalations, incident response, and launch consults on systems serving Claude in production
- Hands-on application and infrastructure security experience, including cloud and containerized environments
- Production-quality coding ability in at least one of Python, Go, Rust, or TypeScript, with a track record of building durable systems rather than one-off scripts
- Practical threat-modeling and vulnerability-identification skills — you've found and reasoned about real bugs in real systems, even if breaking isn't your primary mode
- Demonstrated ability to operate with high autonomy and ambiguity — comfortable being handed a problem and a lot of latitude rather than a spec
- Clear technical communication with both engineers and leadership
- 7+ years in application security, security engineering, or security-focused software engineering
- Already use LLMs as a core part of how you work, with opinions about where they help and where they don't
- Experience securing agentic, code-execution, or LLM-integrated systems specifically
- Prior ownership of a bug bounty program, vulnerability disclosure program, or vulnerability-management infrastructure at scale
- Background building security automation or developer-facing security tooling
- Offensive security or penetration testing experience
- An increasingly autonomous vulnerability pipeline — LLM-driven code analysis finds the issue, scores it for real exploitability, and opens the fix PR, with humans as the review step rather than the author
- Bug bounty operations where Claude handles first-line triage and drafting, and engineers focus on the reports that actually need judgment
- AI-assisted threat modeling that generates intake questions, drafts the model, and recommends which design reviews need a human in the room
- Automated dependency vulnerability remediation across Anthropic's codebase
- The company-wide vulnerability dashboard and SLA enforcement layer every engineering team works against
- Threat models and security architecture for agentic product surfaces — code execution sandboxing, agent identity and delegated auth, tool-use boundaries
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
