About
Deliveroo is a marketplace that issues banking products, lends to merchants, moves instant payouts to couriers, and collects cash on delivery. Its financial products serve millions of couriers and merchants.
Responsibilities
•Build and maintain high-throughput, low-latency Go backend services that score financial events in real time, including payout enrollments, bank account links, credit applications, and account-to-account transfers
•Design end-to-end fraud detection and automated enforcement for financial products, from signal collection to decisions that block fraudulent payouts
•Extend the shared fraud decisioning platform so signals, rules, and models work across all three brands
•Partner with risk analysts, data scientists, and product managers to turn observed fraud patterns into detection and determine whether a rule, model, or product change is the right solution
•Collaborate with account security, payments fraud, and financial product teams, building on their signals and creating clean interfaces
•Contribute to architectural discussions and technical decisions while establishing the fraud infrastructure baseline for financial products, with support from senior engineers
•Write well-tested, observable code and help maintain a high quality bar
Requirements
•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 learning Go quickly
•Working understanding of low-latency, high-throughput distributed systems and willingness to learn to build within a latency budget
•Hands-on experience with SQL and/or NoSQL databases and exposure to event-driven architectures such as Kafka
•Willingness to operate what you build, including sharing on-call duties, with a pragmatic approach to reliability
•Use AI tooling in day-to-day development and critically evaluate its output for correctness and quality
•Product-oriented mindset, responsibility for outcomes, comfort with ambiguity, end-to-end project or feature ownership, clear and proactive communication, collaboration, and an adversarial instinct
Nice to have
•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 AWS or GCP
•Experience across multiple brands, regions, or regulatory regimes
Conditions
The role is based in London, UK.
