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San Francisco, CA | New York City, NY | Seattle, WA
Onsite
Not Available
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.
Data Center Security Engineering (DCSE) owns physical security across Anthropic's data center footprint: the sites, the hardware inside them, and the supply chain that delivers it. The Security Fusion Platform is where physical security signals from across that footprint are correlated and put in front of the analysts who act on them. It carries continuous monitoring, audit evidence, metrics, and analyst response, along with the classification and analytics pipelines that turn sensor data into events. You'll build and own the platform analysts work from.
This is a foundational role. You'll build the software platform that carries a signal from source to analyst decision, ship its first versions, and keep them running in production. The sensors and systems at each site belong to other DCSE engineers; you define the event contract their owners deliver to, and you build the classification and analytics pipelines that run over what those sources produce. Physical security systems engineers own the operations spaces; you own the software that runs in them. You'll work alongside engineers focused on the sites themselves. What you lead, you own end to end: the design, the technical approach, and the result in production.
You'll work with external vendors and integrators, setting requirements and acceptance criteria for what you own and deciding what the team builds itself. We use Claude throughout our engineering workflow and expect you to as well.
This role involves regular travel to data center sites. No security clearance is required. These are critical services, and you'll take part in on-call for them.
Design and build the event bus and normalized event schema: source identity, sequencing, health state, and the adapter contract that owners of each sensor and system feed build to, plus adapters where needed
Build correlation and alerting: the rules and services that turn events from independent sources into alerts an analyst can act on
Build the classification and analytics pipelines: computer vision and multi-sensor fusion, with results landing on the event bus
Build analyst surfaces: the queue, escalation tooling, dashboards, camera viewers, and video wall content a 24/7 watch works from, plus video analytics integration so camera streams arrive on the bus as events
Deliver audit evidence: durable, tamper-evident event history, evidence exports, and the retention and access controls around them
Instrument metrics and self-monitoring: detection rates, nuisance ratios, alert aging, time to resolve; heartbeats and loss-of-telemetry alarms on every feed, tested fail-secure behavior, and change audit on every rule
Deploy across sites: site-local components, central services, and the sync that keeps configuration, rules, and state consistent, then commission each site and hand over to the analysts
Specify the compute the platform runs on (servers, storage, and the platform's network segment) to the team's segmentation and hardening baseline
Write requirements and acceptance criteria for what vendors and integrators deliver, review deliverables against them, and make the call on accepting or rejecting the work
Have built and run event-driven backend systems in production
Are proficient in at least one backend language such as Python, Go, or Rust, and have worked with a message bus or event streaming system such as Kafka
Have owned a system end to end: set the design, made the tradeoffs, shipped it, and answered for it in production
Have integrated with external systems you did not control (vendor APIs, on-prem appliances, video platforms, building systems) and designed for a life beyond any one vendor
Have directed vendor or integrator work: written requirements and acceptance criteria, reviewed deliverables against them, and decided what gets accepted
Design for the failure you won't see coming (a silent feed, a lost network path, a replayed event, a de-tuned rule), know how your system behaves when a source lies or goes quiet, and test for it
Build tools for people who use them under pressure and iterate with those operators
Experience building or operating a security operations platform (SOC, physical security operations, or the detection engineering behind one)
Experience building ML or computer vision inference pipelines over video and sensor streams
PSIM (physical security information management) or VMS (video management system) integration experience, or familiarity with physical access control and building systems data
Experience producing evidence for auditors or assessors: log integrity, retention, chain of custody
Experience using AI-assisted development tooling as a core part of your workflow
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
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.
