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We're hiring a Software Engineer to join the Risk Engineering team, within the Consumer & Business group. The team sits at the forefront of protecting Coinbase and millions of users from fraud and financial risk. We build flexible, scalable, and customizable engineering systems to detect and prevent fraud, incorporating mechanisms for risk decisioning, real-time monitoring, and intelligent mitigation. You'll design, build, and optimize risk detection and mitigation systems that balance technical excellence, system reliability, and business impact — working on some of the most critical and high-throughput services at Coinbase.
What you'll do:
- Build and maintain backend services that power risk detection, fraud prevention, and financial risk mitigation across Coinbase's platform — operating at the scale, speed, and 24x7 nature of crypto markets.
- Own feature delivery end-to-end — from technical design through implementation, testing, deployment, and monitoring — for risk platform capabilities that directly protect users and the business from financial threats.
- Partner with Data Science, ML, and Risk Analysts teams to develop both proactive systems (models, user-facing risk features) and reactive solutions (one-off risk mitigations, incident response tooling) that reduce fraud and financial loss.
- Drive reliability and observability in risk platform services by implementing mechanisms to identify regressions, ensure prompt visibility of issues, and contribute to incident response and post-mortems.
- Contribute to the team's engineering culture by leaving code cleaner than you found it, maintaining high code velocity, participating in code reviews, and building reusable solutions that can be leveraged across the team.
Required Skills and Experience:
- 2+ years of experience in backend software engineering, with a track record of shipping production services in a fast-paced environment.
- Proficiency in at least one backend language (e.g., Go, Ruby, Python, Java) and experience working with relational and/or NoSQL databases (e.g., Postgres, DynamoDB, MongoDB).
- Strong understanding of software design patterns, data structures, and algorithms — with the ability to independently manage complex tasks and work in unfamiliar systems with guidance.
- Experience building or work