Staff + Software Security Engineer (Labs)

Join Anthropic, a leading AI safety and research company, as a Staff + Software Security Engineer in our Security Labs team. In this role, you will work on high-risk, high-reward security projects that aim to address the unique challenges posed by advanced AI technology. You will have the opportunity to shape the future of AI security and make a meaningful impact in the field.

• Own Security Labs projects end to end, from scoping the bet to building the prototype and running it against real workloads.
• Stand up novel security infrastructure quickly, optimizing for what we learn rather than for permanence.
• Work embedded with research and infrastructure teams to test whether their workflows survive proposed changes, and document precisely where they don't.

• We're hiring generalists with rare depth
• You've built things under your own direction, you're comfortable jumping layers when the problem demands it, and you'd rather take a swing at something that might not work than ship the safe incremental thing
• You're a strong software engineer as a baseline, and on top of that you've gone deep in at least one area most engineers don't get near: firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods, reverse engineering, or high-assurance and cross-domain systems
• You think the trajectory of AI matters a great deal, you're not comfortable with how the security side of it is going by default, and you'd rather be on the inside building the answer than watching from outside
• Change your mind when the evidence says to, and are fine being the least-expert person in a room full of specialists
• Have run prototypes or experiments where the goal was answering a hard question rather than shipping a permanent system, including ones that didn't pan out
• Have built and shipped things under your own direction. Maybe you founded a company or research group, maintained an open-source project other people depend on, or shipped research that changed how people in your field work. We weight this far more than where you've worked or for how long
• Write clearly enough to turn weeks of work into a couple of pages someone can act on
• Are comfortable jumping between domains and layers of the stack when the problem calls for it, and have actually done so
• Have a track record of choosing the problem yourself and seeing it through, rather than only executing a plan someone else handed you
• Genuinely care about where AI is heading and want to work on the security problems that determine whether it goes well. This is the most important thing on this list
• Have real depth in at least one area most software engineers don't touch (e.g. firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods and verification, reverse engineering and exploit development, or high-assurance / cross-domain systems)
• Are a strong programmer (Python plus at least one of Rust, Go, or C/C++) and can stand up real infrastructure without that being the interesting part of your week
• Care about defense. Plenty of folks here come from offense and that background is valuable, but what you actually want to spend your time on now is making systems hold up
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• 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
• Familiarity with ML infrastructure (training pipelines, distributed schedulers, inference serving, accelerator hardware) sufficient for grounded conversations with researchers about what their workloads actually need
• Experience inside airgapped or high-side environments (classified networks, cross-domain solutions, ICS/SCADA, financial trading infrastructure) and the operational realities of working in them
• A background in offensive security, red teaming, or vulnerability research, with calibrated intuitions for which threats actually matter
• A history of working in environments built around rapid iteration rather than rigid change control: startups, applied research groups, independent consulting, small security shops