Trust and Safety Engineer
AI platform for creating, deploying, and managing full-stack software through natural-language interaction.
Maintainer signals as of 9/25/2026
Funding history
About Lovable
Lovable lets people describe an idea in plain language and collaboratively build production-grade software. Its platform includes hosting, authentication, payments, integrations, security features, and deployment infrastructure.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Design and ship fraud platforms that protect payments, credits, and free-tier access. Build real-time detection signals, features, scoring, and decisioning; operate feedback loops with chargebacks and support; deploy bot defenses; and measure fraud and attacker-related metrics.
Requirements
- 5+ years of experience building anti-fraud, anti-abuse, or risk systems at consumer scale.
- Backend engineering with Go, Python, or TypeScript.
- Data engineering.
- Fraud campaign disruption.
- Rules engines.
- Real-time feature stores.
- Machine learning scoring.
- Device fingerprinting.
- Behavioral signals.
- Fraud modeling.
- Precision and recall trade-offs.
- LLM-specific abuse experience.
- Chargeback and payments fraud experience.
Responsibilities
- Design and ship the fraud platform.
- Protect payments, credits, and free-tier access from abuse.
- Build real-time detection signals, features, scoring, and decisioning.
- Run feedback loops with chargebacks, support, and trust and safety.
- Label, learn, and redeploy fraud controls weekly.
- Deploy bot defenses across signup, app generation, and publishing.
- Track fraud loss rate, false-positive rate, and attacker time-to-defeat.