Safeguards Enforcement Analyst, Fraud & Scams

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.

As a Safeguards Enforcement Analyst on the account abuse team, you ll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be standing up fraud & scams enforcement as a program: today this work is handled reactively and in fragments — payment fraud, promotional abuse, and scam-pattern enforcement don t yet have a single owner.

You ll be that owner: defining the policy area, building the detection-to-enforcement pipeline, and setting the operating model that a contractor bench can execute against. The surface area is broad: payment fraud (stolen cards, chargebacks, disputes), promotional and credits abuse, and the use of accounts to run scams against third parties.

This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you ll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.

• Define the fraud & scams policy taxonomy and how cases are classified, prioritized, and escalated
• Investigate and dismantle organized abuse rings, converting findings into durable controls
• Stand up proactive fraud detection and customer-facing communication flows for fraudulent organization cases
• Build the dispute and chargeback strategy in partnership with payments and card-network partners
• Quantify fraud losses and control efficacy to drive investment decisions
• Author the contractor playbook for fraud review and own QA of scaled output
• Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows

• Deep payment-fraud experience at a fintech, marketplace, or platform — chargebacks, disputes, card-testing, promotional abuse
• Experience building or significantly scaling a fraud program from an early state, not just operating a mature one
• A working command of payment-network and dispute mechanics, sufficient to make strategy calls on them
• Comfort being the sole owner of an area: prioritizing ruthlessly, shipping iteratively, and asking for help precisely
• Comfort using data (SQL or similar tools) to quantify fraud losses and control efficacy
• Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders
• Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and work streams

• Experience working directly with payment service providers and card networks on fraud strategy
• Experience with scam typologies beyond payments — social engineering, impersonation, platform-mediated scams
• Experience managing vendor relationships in the fraud/risk detection space
• A deep interest in AI safety and responsible technology development
• Experience writing effective prompts for generative AI systems in a content review or enforcement context

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

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…