Golang Backend Engineer, Financial Product Fraud

About the role

Deliveroo, now part of DoorDash, is looking for a Golang Backend Engineer to build fraud protection for its financial products across DoorDash, Wolt and Deliveroo. The team covers fraud wherever money moves through the platform: instant payouts, merchant cash advances and platform-issued banking and wage products. The role is based in London as one of the founding engineering positions, working closely with teams in Helsinki and Berlin.

Key responsibilities

• Build and maintain high-throughput, low-latency Go backend services that score financial events in real time, such as payout enrollments, bank account links, credit applications and account-to-account transfers.
• Design fraud detection and automated enforcement end to end, from signal collection to the decision that blocks a fraudulent payout.
• 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 fraud patterns into shipped detection.
• Work with account security, payments fraud and financial product teams, building on their signals rather than rebuilding them.
• Take part in architectural discussions and technical decisions as the fraud infrastructure baseline is set, with support from senior engineers.
• Write well-tested, observable code and help the team keep a high quality bar.

Required profile

• 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.
• Hands-on experience with SQL and/or NoSQL databases and some exposure to event-driven architectures (Kafka or similar).
• Willingness to run the code, including a share of on-call duty.
• Uses AI tooling in day-to-day development and can critically evaluate its output.

Nice to have

• Experience in fraud, risk, payments, lending or financial crime.
• 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 (AWS, GCP).
• Experience across multiple brands, regions or regulatory regimes.