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. Key responsibilities • 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 Minimum qualifications • 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 workstreams Preferred qualifications • 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 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.