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DeliverooGolang Backend Engineer, Financial Product Fraud
This is a full-time, on-site engineering position in London with Deliveroo, which is now part of DoorDash. The engineer joins a fraud team that is being…
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About This Role
This is a full-time, on-site engineering position in London with Deliveroo, which is now part of DoorDash. The engineer joins a fraud team that is being formed to cover every point where money leaves the company's financial products, such as instant courier payouts, loans to merchants, and banking and earned-wage offerings. Each of those is an area already exposed to losses, and new launches widen it. The London office is…
Job Description
This is a full-time, on-site engineering position in London with Deliveroo, which is now part of DoorDash. The engineer joins a fraud team that is being formed to cover every point where money leaves the company's financial products, such as instant courier payouts, loans to merchants, and banking and earned-wage offerings. Each of those is an area already exposed to losses, and new launches widen it.
The London office is one of the founding engineering hubs for this work and will partner with teams in Helsinki and Berlin. Most of the work is Go backend code that scores financial activity as it happens: payout enrolment, linking of bank accounts, credit requests and transfers between accounts. Engineers own the chain from gathering signals to the enforcement decision that stops a bad payout, and they add to the shared fraud platform that serves all three brands.
Collaboration is central. Engineers team up with analysts who study risk, with data scientists and with product leads to convert observed fraud behaviour into live detection, and with colleagues in account protection, payments-side fraud and financial product groups that provide the underlying signals. The role contributes to architecture choices for this new fraud foundation, calls for well-tested and traceable code, and expects a strong quality standard. The company stresses that a silent failure here means money is lost.
Applicants should have three to six years of professional software experience, including backend services they have launched and maintained in production. A year of production Go is expected, or else solid work in another backend language along with readiness to learn Go quickly. Useful strengths include an understanding of low-delay, high-volume distributed systems, working knowledge of relational or document databases, familiarity with event streaming tools such as Kafka, and readiness to join an on-call rota.
Responsibilities
- Write Go services that handle large volumes with minimal delay and score financial activity in real time
- Own fraud detection and automatic enforcement across the whole path, from collecting signals to blocking a suspicious payout
- Expand the common fraud decision platform so that signals, rules and models can be shared across the three brands rather than rebuilt for each
- Translate patterns noticed by analysts and data scientists into detection that ships, and decide if a rule, model or product change is the best fix
- Use clean interfaces to build on the signals provided by neighbouring security, payments and product teams
- Help shape architecture decisions for the new fraud infrastructure, with guidance from senior engineers
- Write tests and instrumentation for everything shipped, and help keep the team's quality expectations high
Requirements
- Three to six years of professional software engineering, including backend services that you launched and looked after in production
- A year or more of production Go, or substantial work in another backend language with a clear intention to learn Go fast
- Grounded knowledge of distributed systems that must stay fast under heavy throughput
- Comfort designing inside a fixed time budget for each real-time decision
- Practical use of SQL or NoSQL data stores and some acquaintance with event-driven designs such as Kafka
- Readiness to run what you build, taking a share of on-call shifts
- Applies AI tooling as part of everyday work and reviews its output carefully for accuracy and quality
Qualifications
- Past work in lending, payments, risk or fraud teams, or in financial crime, with a focus on transfers of funds or payout misuse
- Practical familiarity with decision-rule tooling, live feature stores or serving ML models within a decisioning flow
- Comfort with Node.js, Python, Java or Kotlin as well as Go
- Knowledge of AWS or GCP cloud environments
- Experience across several brands, regions or regulatory regimes
- Product-focused thinking that cares about the purpose behind the work, comfort with unclear scope, and a mindset that anticipates how attackers operate
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is the role located?
The posting places the role in London, UK, and describes it as on site.
Is the position full-time?
Yes, the posting lists it as a full-time role.
What experience does the posting ask for?
It asks for three to six years in software engineering roles, with at least one year of production Go or solid experience in a different backend language.
Is a salary listed?
The posting does not specify a salary or pay range.
Does the role involve on-call work?
Yes, candidates are expected to be willing to support what they build, including some on-call shifts.
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