Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Claude Code
Communication @ 6
Go @ 6
LLM @ 4
Leadership @ 6
Python @ 6
Rust @ 6
Security @ 6
TypeScript @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
About the role
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.
Responsibilities
- 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
Requirements
- 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
Preferred qualifications
- 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
Representative projects
- 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
Logistics & location policy
- 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. If Anthropic makes an offer, the company will make every reasonable effort to get you a visa, and retains an immigration lawyer to help with this.
Minimum education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
Compensation
- Annual Salary: $320,000 - $485,000 USD