Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
More about our mission and what we offer.
Job DescriptionThe team you will join: Fraud Risk Team
Join the Fraud Risk team, where we are dedicated to preventing fraud before it happens and keeping Wise customers safe in real time. Our mission is to stop fraudulent activity at the point of attempt by running instant checks on transfers and customer profiles, making accurate risk decisions with minimal friction. We build scalable, low-latency systems, improve our detection and decisioning tooling, and partner closely with fraud specialists to continuously raise the bar on prevention using data, automation, and AI-driven signals to reduce losses and protect legitimate customers.
Our vision:
Create an automated, real-time fraud prevention experience that blocks bad activity while keeping genuine customers moving.
Build fast, reliable risk decisioning capabilities for transfers and profiles, optimised for accuracy, latency, and scale.
Foster a strong partnership between fraud prevention specialists and the product/engineering team to translate expert knowledge into effective controls.
Use AI-driven detection and decisioning, and work closely with Data Scientists to productionise models and signals, improving precision, reducing false positives, and lowering operational costs.
What will you be working on?
Real-World Impact: Shape and build the systems that prevent fraud and scams through real-time transfer and profile decisioning.
Technical Ownership: Own the technical roadmap and deliverables of key projects in our prevention domain, delivering them predictably and with clear customer impact.
Domain & Platform Evolution: Build deep expertise across our technical and fraud domains, driving continuous improvements in latency, reliability, and decision quality across our decisioning platform.
System Health: Address technical debt, keep risk within appetite, and enforce Wise's engineering best practices (observability, security, Kafka/DB usage, testing).
Engineering Leadership: Multiply team impact by mentoring engineers, sharing knowledge to eliminate single points of failure, leading onboarding, and interviewing future talent.
Cross-Team Collaboration: Contribute beyond the team through guilds and cross-team engineering efforts to reduce duplicated work across fraud and risk domains.
Overview of the Current Team: The Fraud Risk team is a passionate group of prevention-focused crime fighters based in Budapest and Tallinn. We're a mix of engineers and fraud specialists committed to making Wise a safer platform through fast, accurate decisions on transfers and customer profiles. Our collaborative environment encourages innovation, ownership, and teamwork, making it an exciting place to work on cutting-edge solutions in fraud prevention.
QualificationsQualifications
Engineering Expertise: Strong experience building and operating production systems on Java/JVM, with expert-level knowledge of your technical discipline.
Distributed Systems: Solid understanding of distributed systems and event-driven architectures (Kafka or similar), including designing for low latency, high availability, and scale.
Technical Leadership: A track record of contributing significantly to large, impactful projects and owning their technical direction—from design and RFCs through delivery and long-term operation.
Long-Term System Design: Experience designing systems with long-term iteration and scaling in mind, well-documented API-first interfaces, and a proactive approach to technical debt.
Operational Excellence: Accountability for the reliability, security, and observability of the systems you build, including taking a leading role in incident resolution and post-incident reviews.
Product Mindset: Ability to articulate why something is being built, what customer problem it solves, and what impact to expect, providing valuable feedback on the product roadmap to balance protection with low friction.
Mentorship & Quality: Experience mentoring and coaching other engineers, helping raise the engineering bar through code reviews, design discussions, and best practices.
Collaboration: Excellent communication skills to collaborate effectively across functions (Product, Data Science, Fraud Operations, Analytics).
Nice to Have: Experience with Python, machine learning concepts, deploying models in production, or working with large language models in production.
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Skills Required
- Strong experience building and operating production systems using Java or JVM technologies
- Expert-level knowledge of the relevant engineering discipline
- Understanding of distributed systems and event-driven architectures, including Kafka or similar technologies
- Experience designing low-latency, highly available, scalable systems
- Track record contributing significantly to large, impactful projects and owning technical direction from design through long-term operation
- Experience designing scalable systems with documented, API-first interfaces and proactively managing technical debt
- Accountability for system reliability, security, and observability, including leading incident resolution and post-incident reviews
- Ability to articulate customer problems, product rationale, and expected impact
- Experience mentoring and coaching engineers through code reviews, design discussions, and best practices
- Excellent communication and cross-functional collaboration skills
- Experience with Python
- Knowledge of machine learning concepts
- Experience deploying machine learning models in production
- Experience working with large language models in production
Wise Compensation & Benefits Highlights
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Leave & Time Off Breadth — U.S. materials describe extensive paid leave (PTO, sick time, holidays, “Me Days,” volunteer and compassionate leave) plus a paid six‑week sabbatical after four years. Feedback suggests the time‑off package is a standout element of the offering.
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Parental & Family Support — Benefits information highlights up to 18 weeks of fully paid parental leave in many locations, with clear tenure qualifiers in some markets. Feedback suggests these policies are robust and a notable strength.
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Equity Value & Accessibility — Company and job-posting materials indicate RSUs are a regular part of compensation, with a shift toward RSUs since 2022. Feedback suggests the equity component is a relatively substantial part of total rewards.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
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Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.
