Trust & Safety Engineer

About the role

Join Lovable as a Trust & Safety Engineer to develop, refine, and deploy systems that prevent abuse, fraud, and malicious activities on our platform. You will be responsible for building adaptive, real-time detection mechanisms that safeguard our users and platform integrity. Your work will directly impact millions of users by ensuring a safe and trustworthy environment. The role involves designing scalable solutions, collaborating closely with support, chargebacks, and safety teams, and continuously improving our defenses to stay ahead of evolving threats. As part of our small, talented team based in Stockholm, you will have the opportunity to shape the future of trust and safety at a company that is redefining how software is built and used globally.

Key facts

What you'll do

• Design, develop, and maintain the fraud prevention platform that protects Lovable's payments, credits, and free tier from abuse and misuse.
• Build and optimize real-time detection systems, including signals, features, scoring algorithms, and decision-making processes that operate within milliseconds to prevent fraudulent activities before they reach users.
• Establish and maintain a tight feedback loop with chargebacks, support, and trust & safety teams to label data, analyze incidents, and update detection models on a weekly basis.
• Implement and improve bot detection and prevention measures across various user journeys, including signup, app creation, and content publishing, ensuring legitimate users are not impacted.
• Take ownership of key trust and safety metrics such as fraud loss rate, false-positive rate, and attacker time-to-defeat, and work to optimize these continuously.
• Collaborate with engineering teams to deploy scalable solutions using TypeScript, Python, and Go, ensuring systems are robust and maintainable.
• Monitor system performance, analyze detection effectiveness, and refine algorithms to adapt to new fraud tactics and attack vectors.
• Contribute to the development of rules engines, real-time feature stores, and ML scoring models that enhance detection capabilities.
• Ensure compliance with relevant legal, security, and privacy standards, maintaining high standards of data protection and user safety.
• Document processes, detection strategies, and system architectures to facilitate knowledge sharing and onboarding.
• Work closely with product and engineering teams to integrate trust and safety features seamlessly into the platform.
• Participate in incident response and investigations related to abuse, fraud, or security breaches, providing insights and recommendations.
• Stay informed about the latest trends and techniques in fraud prevention, adversarial attacks, and machine learning applications in trust and safety.

Requirements

• Over 5 years of experience building anti-fraud, anti-abuse, or risk management systems at consumer scale, such as payments, marketplaces, fintech, or large social platforms.
• Strong backend engineering skills with proficiency in Go, Python, or TypeScript, and comfort working close to the data layer.
• Proven experience disrupting sophisticated fraud campaigns and attacks, with knowledge of rules engines, real-time feature stores, ML scoring, device fingerprinting, and behavioral signals.
• Ability to think adversarially: model attacker behavior, develop effective countermeasures, and measure their effectiveness before attackers adapt.
• Pragmatic approach to balancing precision and recall, protecting users from abuse without causing false positives or user frustration.
• Bonus: experience with abuse related to large language models, such as prompt injection at scale, generated-content fraud, or credit farming.
• Bonus: experience with chargeback and payments fraud at companies like Stripe, Adyen, or Braintree at a merchant scale.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and translate insights into actionable solutions.
• Excellent communication skills in English, capable of collaborating across teams and documenting technical strategies clearly.
• Ability to work in a fast-paced environment, prioritize tasks effectively, and ship solutions rapidly.

Nice to have

• Experience working with large language models and understanding of specific abuse vectors such as prompt injection or generated-content fraud.
• Background in payments or fintech fraud prevention, with knowledge of industry standards and best practices.
• Familiarity with legal and compliance issues related to trust and safety, including data privacy and security regulations.
• Prior experience working in high-velocity engineering teams that value ownership, speed, and collaboration.
• Knowledge of data-driven decision-making processes, including metrics tracking and analysis to measure system effectiveness.

Skills & tools

• TypeScript
• Python
• Go
• ML and real-time scoring systems
• Rules engines and feature stores
• Behavioral analytics and device fingerprinting

Practical notes

• This is an on-site role based in Stockholm.
• Candidates are encouraged to submit their applications in English via the company's careers portal.
• Lovable values high ownership, fast shipping, and low-ego collaboration, fostering a culture of innovation and shared responsibility.
• The company is committed to equal opportunity employment and welcomes applicants from diverse backgrounds.
• The role offers an exciting opportunity to work at a company that is at the forefront of enabling anyone to build software with any language, impacting hundreds of millions of users worldwide.

About the company

Lovable is an AI-powered full-stack development platform that turns natural language prompts into production-ready web applications. The platform enables rapid prototyping and deployment.