3 days ago
Stockholm, SwedenSenior
Responsibilities
- Design and ship the fraud platform protecting Lovable’s payments, credits, and free tier from abuse.
- Build real-time detection systems covering signals, features, scoring, and decisioning that operate in milliseconds.
- Develop bot defenses across signup, app generation, and publishing while minimizing impact on legitimate users.
- Create feedback loops with chargebacks, support, and Trust & Safety to label, learn, and redeploy improvements weekly.
- Own fraud loss rate, false-positive rate, and attacker time-to-defeat metrics.
Requirements
- 5+ years of experience building anti-fraud, anti-abuse, or risk systems at consumer scale in payments, marketplaces, fintech, or large social platforms.
- Strong backend engineering experience with Go, Python, or TypeScript and comfort working close to data.
- Experience disrupting sophisticated fraud campaigns and attacks.
- Knowledge of rules engines, real-time feature stores, ML scoring, device fingerprinting, and behavioral signals.
- Ability to model attackers, ship countermeasures, and measure outcomes before attackers adapt.
- Pragmatic understanding of precision/recall trade-offs and protecting users without unnecessarily penalizing them.
- Bonus experience with LLM-specific abuse, including prompt injection at scale, generated-content fraud, or credit farming.
- Bonus experience with chargeback and payments fraud at a Stripe-, Adyen-, or Braintree-scale merchant.
Tech Stack
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