Trust & Safety Engineer

Lovable

Stockholm, Sweden

On-site

Who this role is best for

Geared toward experienced engineers comfortable with real-time fraud detection systems, this role favors candidates with a background in payments or social platforms and a preference for in-office collaboration in Stockholm.

Best fit for

Experienced engineers with a background in payments or social platforms and a track record of disrupting fraud campaigns.
— “Experience with disrupting sophisticated fraud campaigns and attacks”
Candidates who can balance precision and recall in high-stakes environments while maintaining low false-positive rates.
— “Pragmatic about precision/recall trade-offs. You protect users without punishing them.”
Individuals who have worked on real-time systems and are familiar with machine learning scoring and behavioral signals.
— “Experience with rules engines, real-time feature stores, ML scoring, device fingerprinting, and behavioral signals.”

Things to consider

Application must be in English, which may be a barrier for non-native speakers.
— “Please submit your application in English - it’s our company language”
The role demands high velocity and low-ego collaboration, which may not suit slower-paced or individualistic work styles.
— “culture rooted in extreme ownership, high velocity, and low-ego collaboration”

How to stand out

Highlight your experience with real-time detection systems and how you've adapted to evolving fraud patterns.
— “You think in adversaries: you can model an attacker, ship a counter, and measure it before they adapt.”
Demonstrate familiarity with backend engineering in Go, Python, or TypeScript and working closely with data.
— “Strong backend engineering - Go, Python, or TypeScript - and comfort working close to the data.”
Emphasize experience with bot defenses and adaptive systems in platform or marketplace contexts.
— “Stand up bot defenses across signup, app generation, and publishing - without breaking legitimate users.”
Position yourself as someone who owns metrics and drives continuous improvement through weekly re-deployments.
— “Run a tight feedback loop with chargebacks, support, and trust & safety to label, learn, and re-deploy weekly.”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design and ship the fraud platform
build real-time detection
stand up bot defenses
own the metrics that matter

Typical background

5+ years building anti-fraud, anti-abuse, or risk systems

Skills & requirements

Required

Backend EngineeringGoPythonTypeScriptAnti-fraud SystemsReal-time Feature StoresML ScoringDevice FingerprintingBehavioral Signals

Preferred

Llm-specific AbuseChargeback And Payments Fraud

Stack & domain

GoPythonTypeScriptAnti-fraudAnti-abuseRisk SystemsReal-time Feature StoresML ScoringDevice FingerprintingBehavioral SignalsLeadershipProblem-solvingCommunicationFinanceHealthcareAI

About the role

Original posting from Lovable via Ashby

TL;DR Millions of people build on Lovable every month. A small fraction try to abuse it. You'll build the adaptive systems that stop monetary fraud, platform abuse, and bot attacks before they reach our users.
WHY LOVABLE?
Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we’re just getting started.
We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world.
Lovable is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software.
WHAT WE'RE LOOKING FOR
5+ years building anti-fraud, anti-abuse, or risk systems at consumer scale (payments, marketplaces, fintech, or large social platforms).
Strong backend engineering - Go, Python, or TypeScript - and comfort working close to the data.
Experience with disrupting sophisticated fraud campaigns and attacks, knowledge of rules engines, real-time feature stores, ML scoring, device fingerprinting, and behavioral signals.
You think in adversaries: you can model an attacker, ship a counter, and measure it before they adapt.
Pragmatic about precision/recall trade-offs. You protect users without punishing them.
Bonus: experience with LLM-specific abuse (prompt injection at scale, generated-content fraud, credit farming) or with chargeback and payments fraud at a Stripe/Adyen/Braintree-scale merchant.
WHAT YOU'LL DO
Design and ship the fraud platform that protects Lovable's payments, credits, and free tier from abuse.
Build real-time detection: signals, features, scoring, and decisioning that act in milliseconds.
Run a tight feedback loop with chargebacks, support, and trust & safety to label, learn, and re-deploy weekly.
Stand up bot defenses across signup, app generation, and publishing - without breaking legitimate users.
Own the metrics that matter: fraud loss rate, false-positive rate, attacker time-to-defeat.
About your application
Please submit your application in English - it’s our company language, so you’ll be speaking lots of it if you join
We treat all candidates equally - if you’re interested, please apply through our careers portal

Source: Lovable careers (Ashby)