Level

Anthropic

Policy Design Manager, Conventional Weapons

Anthropic is hiring a Policy Design Manager, Conventional Weapons in San Francisco, New York and Washington DC, United States. It pays $245k-$285k a year and Level rates it ; you can apply on Anthropic.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
  • Some of the work can be done remotely, according to the posting.
  • The posting mentions visa sponsorship.
  • The posting mentions AI safety, AI research and policy design among its tools and skills.
  • Anthropic has 680 other open roles on Level.

AI in this role

Own conventional weapons policy, threat models, and evaluations for AI safety and guardrails at Anthropic.

ai-safetyai-researchpolicy-designthreat-modelingsafety-evaluationsrisk-management

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. 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

Anthropic's Safeguards organization builds the policies, evaluations, and enforcement systems that define and hold the limits on how Claude can be used. In this role, you'll own our conventional weapons work.

Defining a crisp boundary between acceptable and harmful requests in this domain is difficult, because the underlying components are dual-use: the same capabilities that serve civilian engineering and research can also contribute to a weapons system. Building the threat models, evaluations, and detection systems that hold that boundary is the core of this role.

Conventional weapons are increasingly defined by software, and the risks reach well beyond firearms: from a model operating a weapons system or writing guidance code, to the weaponization of dual-use platforms. The role spans every weapon class, up to autonomous systems that select and engage targets without human authorization.

You will help define the line between prohibited weapons development and legitimate research and engineering work, and how to operationalize the distinction. This will include translating technical judgment into principles that engineers can implement and enforcement teams can act on.

Key responsibilities

  • Own and maintain Anthropic's conventional weapons policy, defining the boundary between the activities our models should and should not support

  • Build the threat models and evaluations that measure how our models could contribute to weapons development, including the software and autonomy components that define modern weapons systems, and keep them current as the technology and its misuse evolve

  • Partner with engineering to turn the policy into model guardrails, detection systems, and enforcement tooling

  • Serve as the subject-matter expert for escalations involving conventional weapons content, including rapid response to emerging risks

  • Build shared understanding of the policy across product, engineering, legal, and leadership, communicating its reasoning to technical and non-technical audiences

  • Engage external experts as well as government and industry partners, and translate that engagement into stronger policy and enforcement

Minimum qualifications

  • Have deep, applied expertise in weapons systems and can translate complex technical evidence into sound policy judgments

  • Experience in a relevant setting, such as a service research laboratory, a defense research or innovation agency, or a company that designs or builds weapons systems

  • Can write clear, operationally precise policy and explain complex technical topics to non-specialist audiences

  • Understand the legal frameworks governing weapons and their transfer, and can craft policy that holds up across jurisdictions

  • Can do rigorous technical analysis of weapons systems using only open sources

  • Are comfortable with ambiguity and drawn to problems that have no established playbook

  • Are motivated by preventing misuse without obstructing the legitimate work in the field

Preferred qualifications

  • A working understanding of machine learning and large language model fundamentals

  • Hands-on engineering experience in a weapons-relevant technical domain, such as systems engineering, robotics and autonomy, guidance/navigation/control, sensors and signal processing, aerospace or mechanical engineering, materials and energetics, or embedded software

  • Hands-on experience applying arms export controls (ITAR/EAR) or international arms-control regimes

  • Experience building or evaluating classifiers, including LLM-based ones, and reasoning about precision and recall for rare, high-consequence categories

  • Trust & safety or product policy experience at a technology platform

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.

Annual Salary:$245,000—$285,000 USD

Logistics

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.

How we're 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. 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.

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 about our policy for using AI in our application process.

How we rate this

Policy Design Manager, Conventional Weapons at Anthropic rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI SafetyAI ResearchPolicy DesignThreat ModelingSafety EvaluationsRisk Management

Questions you could be asked

  1. How do you think about the risk of an AI system in this kind of role failing silently?
  2. Tell me about a research question you investigated. What did you find?
  3. Tell me about a project where policy design was part of your work. What did you do?
  4. Tell me about a project where threat modeling was part of your work. What did you do?
  5. Tell me about a project where safety evaluations was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Safety, AI Research, Policy Design, Threat Modeling, and Safety Evaluations. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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