Golang Backend Engineer, Financial Product Fraud

London · London, United Kingdom - Deliveroo · 1+ years experience · Full-time · Posted Sep 29, 2026

At a glance

Deliveroo is looking for a Backend Engineer (Golang) for the Financial Product Fraud team to build protection for new financial products.
You will design and ship real-time detection and automated enforcement for financial products across DoorDash, Wolt, and Deliveroo.
The role involves building high-throughput, low-latency backend services as one of the founding engineering roles in the London hub.

Build and maintain high-throughput, low-latency backend services in Go that score financial events in real time, including payout enrollments, bank account links, credit applications, and account-to-account transfers.
Design fraud detection and automated enforcement for financial products end to end from signal collection through to the decision that blocks a fraudulent payout.
Build on and extend a shared fraud decisioning platform so signals, rules, and models work across DoorDash, Wolt, and Deliveroo.
Partner closely with risk analysts, data scientists, and product managers to turn observed fraud patterns into shipped detection.
Work across team boundaries with account security, payments fraud, and financial product teams using clean interfaces.
Contribute to architectural discussions and technical decisions as the fraud infrastructure baseline is established for financial products.
Write well-tested, observable code and help the team hold a high quality bar.

3 to 6 years of professional software engineering experience, including backend services shipped and owned in production.
1+ years of production experience in Golang, or strong experience in another backend language and enthusiasm for picking Go up quickly.
A working understanding of low-latency, high-throughput distributed systems.
Hands-on experience with SQL and/or NoSQL databases.
Some exposure to event-driven architectures such as Kafka or similar.
Willingness to operate what you build, including a share of on-call, with a pragmatic approach to reliability.
Uses AI tooling in day-to-day development and can critically evaluate its output for correctness and quality.

Experience in fraud, risk, payments, lending, or financial crime, especially money movement fraud, bank account linking fraud, payout abuse, or lending fraud.
Experience with rules engines, real-time feature stores, or ML model serving in a decisioning path.
Background in Kotlin, Java, Python, or Node.js alongside Go.
Familiarity with cloud infrastructure such as AWS or GCP.
Experience working across multiple brands, regions, or regulatory regimes.

Role is based in London, UK as part of the founding engineering roles in the London hub.