Software Engineer, Backend (Consumer - Risk)

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 working with high-throughput, low-latency systems — or a strong foundation in distributed systems fundamentals (APIs, event-driven architectures, cloud infrastructure).
• Clear written and verbal communication skills; ability to collaborate effectively across engineering, product, data science, and risk operations stakeholders.
• Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.
• Experience with risk, fraud detection, or payment systems (ACH, cards, crypto) and associated fraud patterns.
• Familiarity with cloud platforms (AWS, GCP), containerization (Docker, Kubernetes), and event