Join an innovative technology environment building large-scale cloud infrastructure that powers the integral AI economy. As Product Manager – Anti-Fraud, you will lead the development of products and systems designed to detect, prevent, and respond to fraud across the entire customer lifecycle. Working at the intersection of Trust & Safety, Payments, Risk, Data Science, and Engineering, you will turn sophisticated risk problems into scalable product solutions. Own the tools and workflows that enable analysts and data scientists to define, test, deploy, and monitor detection rules and machine learning models, with appropriate safeguards and audit trails. Strengthen fraud monitoring and incident detection: Coordinate with Trust & Safety, Engineering, and Data Science teams to triage active incidents, establish ownership, mitigate risks, and participate in post-incident reviews. Write clear product requirements documents (PRDs) and technical specifications that transform ambiguous fraud and abuse problems into actionable engineering and data science deliverables. Partner with Analytics and Data Science teams to define detection problems, establish data labels and success criteria, and determine when rule-based systems or machine learning approaches are most appropriate. Run experiments and monitor performance: Collaborate with Legal and Compliance teams to align fraud prevention and enforcement mechanisms with payment-network requirements, KYC/AML obligations, and data privacy standards. Comfortable working with data, using SQL or equivalent analytical tools, and interpreting performance metrics to guide product decisions. Understanding of payment fraud, chargebacks,



identity verification, KYC/AML processes, and risk signals such as device fingerprinting, transaction velocity, IP reputation, and network behavior. Ability to collaborate effectively with Engineering and Data Science teams and engage in technical discussions about detection signals, data features, system behavior, and model performance. Data-driven decision-making: Exposure to cloud infrastructure, SaaS, marketplaces, fintech, or other technology-driven platforms with complex risk and operational requirements. Ability to make sound decisions in ambiguous situations, assess competing priorities, and balance security, business performance, compliance, and user experience. Ability to respond effectively to emerging threats, prioritize urgent issues, coordinate mitigation efforts, and turn incident findings into lasting product improvements. Familiarity with ML-based fraud detection and the operational lifecycle of models, including monitoring, drift detection, and retraining. Cloud and compute abuse prevention: Experience addressing abuse patterns specific to cloud or GPU platforms, including unauthorized mining, credential stuffing, account farming, and systematic exploitation of free-tier resources. Career development: Work alongside talented professionals across Product, Engineering, Data Science, Risk, and Trust & Safety. Contribute to AI infrastructure and develop solutions that protect critical cloud resources and legitimate customers. Collaborate with diverse teams and stakeholders in a global technology setting. Explore emerging fraud prevention techniques, machine learning applications, and new approaches to cloud security.

📌 Product Manager (Madrid)
🏢 Jobgether
📍 Madrid