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About Nebius :
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
We run a large-scale GPU cloud and AI infrastructure platform. Fraud and abuse — stolen payment cards, fake sign-ups, compute mining, credential abuse, and coordinated free-tier exploitation — directly threaten platform economics, capacity availability for legitimate customers, and our standing with payment providers and cloud partners.
As Product Manager, Anti-Fraud, you own the product roadmap for the systems that detect, prevent, and respond to fraud and abuse across the customer lifecycle — from onboarding and payment through to ongoing consumption. You sit at the intersection of Trust & Safety, Payments/Billing, Risk, Data Science, and Product Engineering, and you balance two goals in constant tension: stop bad actors and keep friction near zero for real customers.
Your responsibilities will include:
Own the end-to-end anti-fraud product roadmap: signup/KYC checks, payment fraud detection, account takeover protection, and compute-abuse (e.g., crypto mining, resource reselling) prevention.
Own the rules and risk-scoring surfaces — the tooling that lets analysts and data scientists define, test, and deploy detection rules and ML models with clear guardrails and audit trails.
Own the manual review and case-management experience for the Trust & Safety operations team, including queues, evidence views, and action workflows (block, limit, step-up verification, release).
Own customer-facing friction points — verification flows, step-up challenges, and appeals — designed to minimize false positives and protect the legitimate user experience.
Identify fraud and abuse incidents early — define the signals, alerts, and thresholds that surface incidents before they scale, and own the detection surface that flags them.
Participate in incident reviews and post-mortems, capturing root causes and turning each finding into concrete improvements to detection rules, models, and the roadmap.
Ensure timely response to active incidents — drive fast triage, clear ownership, and mitigation, working alongside Trust & Safety, Engineering, and Data Science to contain impact.
Write clear PRDs and specs that translate fuzzy risk problems into shippable engineering and data-science work.
Partner with Analytics team on detection models — defining the problem, labels, and success criteria, and deciding where rules vs. ML are the right tool.
Run experiments and monitor rollouts, watching both fraud-catch metrics and false-positive / customer-friction impact.
Work with Legal/Compliance to keep detection and enforcement aligned with payment-network rules, KYC/AML expectations, and data-privacy requirements.
Track and report on fraud loss, chargeback rate, false-positive rate, review throughput, and time-to-detection.
We expect you to have:
Proven product management experience in fraud, risk, trust & safety, or payments.
Strong analytical skills — comfortable with data, SQL or equivalent, and reasoning about precision/recall trade-offs and metrics.
Ability to make decisions under ambiguity and to balance security, business, and customer-experience priorities.
Solid collaboration with engineering and data science; you can hold a technical conversation about signals, features, and model behavior.
Exposure to cloud, SaaS, marketplace, fintech, or infrastructure products.
Understanding payment fraud, chargebacks, KYC/AML, or device/network signals (fingerprinting, velocity, IP reputation).
It would be an added bonus if you have:
Familiarity with ML-based detection systems and their operational lifecycle (drift, retraining, monitoring).
Experience with abuse patterns specific to compute or GPU platforms (mining, credential stuffing, free-tier farming).
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius :
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.