This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We’re looking for an Anti-Abuse Automation Engineer to help build and scale the systems that protect Vercel’s platform from fraud and abuse. Our Trust & Safety Engineering team sits at the intersection of product, infrastructure, and risk, tackling challenges across financial fraud, phishing, malware, CSAM, platform abuse, and IP and DMCA enforcement. In this role, you will not just investigate abuse, you will turn insights into systems. You will design detection logic, build automation, and develop workflows that proactively identify and stop bad actors at scale. Working closely with Operations, Product, Finance, and Engineering, you will play a key role in shaping how Vercel prevents fraud, reduces risk, and protects developers and businesses on our platform.
Job Responsibility:
Investigate and proactively identify abuse vectors driving financial loss and platform risk (e.g., payment fraud, account abuse), translating findings into scalable detections
Build, iterate on, and operate internal fraud detection tooling, rules, and anomaly alerting systems to enable high-signal, automated enforcement
Design and continuously refine operational workflows and automation to scale fraud prevention while reducing manual investigation overhead
Partner cross-functionally with Operations, Engineering, Product, and Finance to prioritize risks and ship effective fraud mitigation solutions
Act as a key stakeholder in incident response, leading fraud investigations and developing durable mitigation and prevention strategies
Requirements:
3+ years in fraud and abuse detection within Trust & Safety, with a strong focus on payment and financial fraud (e.g., account takeovers, payment abuse, chargebacks, promo abuse)
Strong proficiency in SQL and experience navigating large, complex datasets to investigate fraud, generate insights, and build detection logic
Designed and implemented automation using scripting and AI tools (LLMs, low/no-code platforms) to streamline investigations and increase enforcement throughput
Built and maintained detection logic (rules, heuristics, risk signals), translating investigative insights into scalable, automated workflows
Owned the iteration of enforcement and restriction strategies, optimizing for precision, coverage, and loss prevention while minimizing false positives and customer friction
Partnered cross-functionally with engineering, data science, and risk teams to productionize detections and integrate ML/LLM capabilities into fraud prevention pipelines
Nice to have:
Experience detecting and mitigating abuse in developer platforms (e.g., API abuse, free tier exploitation, bot-driven signup or usage abuse)
Familiarity with fraud patterns in cloud infrastructure, SaaS, or edge platforms (e.g., resource abuse, billing evasion, account farming)
Experience leveraging signals from network, device, and usage patterns (IP intelligence, velocity, behavioral anomalies) to detect sophisticated abuse
Comfort working in fast-moving, product-led environments, rapidly shipping detections and iterating alongside engineering teams
What we offer:
Competitive compensation package, including equity
Inclusive Healthcare Package
Learn and Grow - we provide mentorship and send you to events that help you build your network and skills
Flexible Time Off
We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed