2 months 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
Categories
About Lovable
Lovable builds an AI-native software creation platform that lets people build apps and websites by chatting with AI, along with tools such as gptengineer.app. It serves solopreneurs, small businesses, and enterprise teams, and users have created over 60 million projects since its November 2024 launch, with customers including Adidas and Zendesk. The company is privately held and headquartered in Stockholm.