golang engineer for financial products

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.

• 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

• 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
• Будет плюсом: 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

• The role is based in London, UK