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San Francisco, California, United States
Hybrid
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.
Claude is trained and served on hardware in data centers Anthropic operates and in sites partners build and run for us. DCSE secures that footprint: the sites, the hardware moving through them, and the people and vendors who touch it. You'll be the engineer who owns autonomous systems across that footprint as one security domain, from both sides: drones, ground robots and automated vehicles for patrol, inspection and moving hardware, including the security of that automation inside secure areas, and the detection systems that tell us what is flying over or operating near a site uninvited.
You set the approach, select and integrate the platforms and sensors, write the requirements vendors build to, and run what you ship, from the operating model where operators assign missions and machines carry them out to the playbook that turns a detection into an identified track and a well-evidenced handoff to whoever holds authority over the airspace. Interdiction is not part of this role. The goal is security that runs itself: coverage, fleet health and evidence verified continuously, with tools and AI agents doing the routine triage. We favor simple, standard controls and tools that can be verified over elaborate ones. We use Claude throughout our engineering workflow and expect you to as well.
You'll work with the rest of DCSE, including its physical security systems engineers and the engineers on its security monitoring platform, with Anthropic's data center operations and legal teams, and directly with site operators, equipment vendors and aviation and public safety authorities. The role is based in San Francisco, with remote applicants in the US considered, and involves regular travel to data center sites, which are critical infrastructure.
Autonomous security and inspection systems: own the drones, ground robots and other autonomous platforms for perimeter patrol, incident response and infrastructure inspection: platform selection, operating model, operator qualification, maintenance, and the data path from machine to analyst
Tools, automation and AI agents: build the integrations that carry detections, tracks, telemetry and fleet health into the team's security monitoring platform, and the tools and agents that triage detections, check fleet health and assemble evidence. When a review keeps costing people time, you build the tool or agent that retires it
Detection of uncrewed systems: engineer the sensing that tells us what is flying over or operating near a site, what it is and who needs to know: sensor selection and evaluation against live targets, per-site coverage, classification and false-alarm handling, and the playbook from first detection to handoff, with evidence retained
Security of site automation: engineer the controls on automated vehicles, robots and similar machines that move hardware or work inside secure areas: identity and access, network isolation, what they may record and where it goes, fail-secure behavior, their place in chain of custody, and acceptance before they enter a site
Regulatory and site constraints: establish what we may sense, fly, drive, record and retain at each site, partner-operated sites included, under the aviation, spectrum, privacy and safety rules that apply there, with the waivers and approvals that extend it and coordination with local authorities set up before it is needed
Health monitoring: define and test heartbeats, loss-of-coverage and lost-link alarms and fail-secure behavior, so a silent sensor or machine shows as a fault, not a quiet day
Vendor requirements and acceptance: write the requirements, evaluate against live flights and runs, and hold vendors to what they ship
Have engineered autonomous or sensing systems in the field (drones, ground robots, automated vehicles, or RF, radar or optical detection sensors): selected, integrated or secured them for an operation other people relied on, and verified what they actually do against real targets or runs rather than a datasheet
Have integrated systems you did not build (vendor APIs, SDKs, appliances, machine and sensor telemetry) into a platform that outlives any one of them
Read and review code, design the data systems behind security tooling, and build automation (often with AI coding agents) using Git and code review
Have done this work hands-on for data centers, critical infrastructure or a large hardware fleet
Have designed inside a regulatory or safety constraint (aviation, spectrum, privacy, machine safety or similar) and can show the decision it drove
Own a domain end to end: set the approach, carry it through with vendors, site operators, partners and authorities, and run it as something people depend on every day
Remote pilot certification (for example FAA Part 107) and experience flying beyond visual line of sight under a waiver or exemption
Experience with counter-drone (counter-UAS) detection, airspace surveillance or air traffic data systems
Experience running a robot, drone or automated-vehicle fleet in an industrial, logistics or data center setting: fleet management, mission planning, safety cases
Experience securing embedded, operational technology or robotic systems: device identity, network segmentation, update control, logging
Experience with physical security operations at large sites, with law enforcement or aviation authorities, or at sites you did not fully control: cloud, colocation or GPU cloud operators
Have built AI agents or automation that replaced recurring manual work
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.
