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 DescriptionAbout the role:
At Wise, we move money for millions of people around the world — and we take that responsibility seriously. Our AML (Anti-Money Laundering) Handling team builds the internal tooling and investigative systems that help Wise detect, investigate, and report financial crime, keeping our platform safe for every customer who relies on us.
We're looking for a Software Engineer with strong front-end engineering skills to help us build and improve the tooling our AML investigation agents use every day. From the interfaces agents use to review suspicious activity, to the GenAI-powered features that augment their investigations, your work will directly contribute to making Wise a safer place for everyone.
What You'll Work On:
You'll be embedded in our AML Handling product engineering team, working across the full stack of our back-office investigative systems that AML investigation agents rely on globally to identify and act on financial crime.
Specifically, you can expect to:
Build and improve investigative workflows end-to-end — Owning features from back-end data services through to the front-end interfaces agents use, with the goal of meaningfully reducing case handling time and improving decision quality.
Integrate GenAI capabilities into agent tooling — We're actively embedding LLM-powered features directly into our investigative flows. You'll help build the pipelines, APIs, and interfaces that make these features reliable and trustworthy.
Drive UX improvements across our investigative suite — Identifying and eliminating repetitive, redundant agent actions; improving how different systems integrate with each other; and pre-filling data intelligently by connecting front-end experiences to existing back-end data sources.
Build and maintain back-end services — Contributing to the services that power case management, agent queues, automation logic, and data flows — ensuring they are reliable, observable, and scalable as our operations grow.
Contribute to access control and security improvements — Helping ensure agents only see the customer data relevant to their active case assignment, closing a high-priority security vulnerability that protects both our customers and the integrity of our investigations.
Instrument and analyse agent behaviour — Building front-end analytics and back-end data models that allow us to identify bottlenecks, measure the impact of our work, and prioritise improvements with confidence.
Contribute to platform campaigns and tech health — Participating in company-wide engineering initiatives such as framework upgrades, service migrations, and on-call vendor transitions, keeping our systems reliable and secure.
Additional Information
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 front-end engineering skills
- Build end-to-end investigative workflows connecting front-end interfaces to back-end data services
- Integrate GenAI/LLM capabilities into production pipelines, APIs, and interfaces
- Design and maintain reliable, observable, scalable back-end services (case management, queues, automation)
- Contribute to access control and security improvements to protect customer data
- Instrument and analyse agent behaviour using front-end analytics and back-end data models
- Participate in platform initiatives such as framework upgrades, service migrations, and on-call transitions
What the Team is Saying
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Wise Compensation & Benefits Highlights
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Leave & Time Off Breadth — Global minimum of 33 paid days off (36 in U.S. hubs) plus a 6‑week paid sabbatical every four years and extras like volunteer or “Me” days indicate substantial time‑off depth.
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Parental & Family Support — A global minimum of 18 weeks fully paid parental leave for birth or adoption after one year, along with adoption and fertility support, underscores robust family support.
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Flexible Benefits — Work‑from‑anywhere up to 90 days per year after six months and flexible working principles provide notable geographic mobility and scheduling latitude.
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.
