Backend Engineer

Key Highlights

• Adaptive adversaries. Fraudsters continuously change tactics, which means backend systems must support rapid iteration, safe rollouts, and real-time feedback loops  without breaking downstream consumers.
• Data sparsity and imbalance. Only a tiny fraction of events are fraudulent, but the systems handling them must be correct, auditable, and resilient across massive volumes of noisy, evolving data.
• Latency and scale constraints. Risk decisions must be made in tens of milliseconds across hundreds of millions of events per month, while keeping infrastructure costs predictable and failure modes well understood.
• Build and own Python/Django services that sit at the heart of Risk Decisioning and Execution.
• Model complex fraud/risk data in Postgres; write queries and aggregations that scale to billions of records.