Security Labs Engineer

About Anthropic

Anthropics 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

Frontier AI is on track to be among the most consequential and most adversarially-targeted technology in the world. The capability curve is steep the adversaries who want these systems are extremely well-resourced and the security bar this will eventually require is well beyond where the industry operates today. Incremental hardening alone is not going to close that gap so we need breakthroughs and a group of people to go find them.

Security Labs is that team. We run a portfolio of high-risk high-expected-value security projects: the work that seems impractical until someone optimistic and stubborn enough actually tries it. Projects run on the order of weeks rather than quarters and each one is either handed off to the Anthropic team that will own it in production or wound down with a writeup of what we learned. We expect a meaningful fraction of our bets not to land.

This is an experimental team and we expect a meaningful fraction of our bets not to land; the team itself is on a prove-out engineers in this role need to be comfortable taking risks. If a 30% project success rate with that much ambiguity sounds uncomfortable or spending your time looking into uncharted and chaotic territory isnt frightening and exciting this probably isnt the right fit. There are other places in Anthropic Security doing important work with more structure less risk and more productive paths to positive outcomes.

The questions were trying to answer include:

• Can our core research workflows survive extreme isolation
• Can we replace trust with cryptographic guarantees
• Can the models themselves become our most effective security control
• What would it actually take to defend against a tier-1 state adversary and how much of that can we build now

Who were looking for. Were hiring generalists with rare depth. Youre a strong software engineer as a baseline and on top of that youve gone deep in at least one area most engineers dont get near: firmware or hardware security applied cryptography OS / kernel / hypervisor internals formal methods reverse engineering or high-assurance and cross-domain systems. Youve built things under your own direction youre comfortable jumping layers when the problem demands it and youd rather take a swing at something that might not work than ship the safe incremental thing. You think the trajectory of AI matters a great deal youre not comfortable with how the security side of it is going by default and youd rather be on the inside building the answer than watching from outside.

Current Project Areas

The portfolio changes as we learn. The kinds of bets currently in flight or queued:

• Standing up a prototype high-assurance research cluster: running real Anthropic training and research workloads under extreme isolation and physical security controls and finding out exactly where productivity breaks and what wed need to invent to get it back
• Provable inference: cryptographic verification (zero-knowledge proofs attestation chains) that a given output came from a specific model running specific code replacing trust us with math
• Swapping our container runtime for a hypervisor-isolated microVM substrate across the fleet so a compromised host cant touch workload integrity
• Compiling an ML kernel through a formally verified pipeline where every lowering step carries a machine-checked proof of equivalence making compilation-layer sabotage mathematically detectable
• Regenerating clusters: automation that spins up a purpose-built cell runs a workload and tears the whole thing down on a TTL measured in hours so attacker persistence has an expiry date
• Using Claude itself to drive security work end to end: threat modeling new compute platforms rewriting critical services to zero external dependencies running the test equipment that validates what hardware datasheets claim

Part of your job is deciding what comes next. We hire people we trust to pick good bets and project selection is owned by the engineers doing the work.

What Youll Do

• Own Security Labs projects end to end. Youll scope the bet build the prototype run it against real workloads and bring it to either a hand-off or a documented exit
• Stand up novel security infrastructure fast (isolated clusters attestation chains hypervisor and runtime work verification tooling) optimizing for what we learn rather than for permanence
• Find the receiving team early bring them along while you build and hand them something they actually want to own
• Work embedded with research and infrastructure teams (Pretraining RL Inference Compute) to test whether their workflows survive what youre proposing and document precisely where they dont
• Turn experimental results into short writeups that shape Anthropics long-term security architecture and into costed contingency plans we could execute on short notice
• Help pick the next round of bets and influence the industry to get better along the way

You May Be a Good Fit If 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 dont 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)
• 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 youve worked or for how long
• Have a track record of choosing the problem yourself and seeing it through rather than only executing a plan someone else handed you
• Are comfortable jumping between domains and layers of the stack when the problem calls for it and have actually done so
• Have run prototypes or experiments where the goal was answering a hard question rather than shipping a permanent system including ones that didnt pan out
• Write clearly enough to turn weeks of work into a couple of pages someone can act on
• Change your mind when the evidence says to and are fine being the least-expert person in a room full of specialists
• 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
• 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

Strong Candidates May Also Have

• 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
• Familiarity with ML infrastructure (training pipelines distributed schedulers inference serving accelerator hardware) sufficient for grounded conversations with researchers about what their workloads actually need
• A history of working in environments built around rapid iteration rather than rigid change control: startups applied research groups independent consulting small security shops

What We Care Less About

• Years of experience. We level on signal and on what youve built not tenure.
• Whether youve built large-scale distributed systems or worked at a big company. If you learn fast and youve shipped real things thats enough.

Location

This role is based in our San Francisco office (500 Howard St). Several Labs projects involve physical secure facilities on-site so expect to be in-office more frequently than Anthropics standard 25% hybrid baseline.

We Encourage You to Apply

Not all strong candidates will meet every qualification listed above. Research shows that people from underrepresented groups are more likely to talk themselves out of applying. If this work interests you and you have most of what were looking for wed like to hear from you.

We believe AI systems have profound social and ethical implications and we think diverse perspectives make our work better. We actively work to build a team that reflects a range of backgrounds and experiences.

Deadline to Apply:None applications will be received on a rolling basis.

Logistics

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

How were different

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. Were 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.

Come work with us!

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 aboutour policy for using AI in our application process.