Staff Software Engineer, Backend - FinHub (Transfers)

Coinbase is hiring a Staff Software Engineer for the FinHub Transfers team. The role owns the architecture and reliability of systems that move crypto and fiat funds, while leading cross-team initiatives that improve the platform for Coinbase products and customers.

Responsibilities:

• Own the technical architecture of Transfers' fund movement systems, driving design decisions on distributed system structure, correctness guarantees, and scalability across crypto and fiat rails
• Lead complex, cross-team engineering initiatives end-to-end, partnering with Payments, Trading, and product engineering teams to deliver new fund movement capabilities and platform improvements
• Drive the evolution of Transfers' backend infrastructure using modern cloud-native patterns, proactively identifying scaling bottlenecks and architecting solutions before they impact customers
• Establish engineering standards, code review practices, and architectural patterns that raise the quality bar across the team and reduce operational risk in high-correctness financial systems
• Mentor engineers across levels on system design, distributed systems best practices, and building production services where financial integrity and reliability are non-negotiable

Requirements:

• 8+ years building and operating large-scale distributed systems in production, with demonstrated experience owning architectural direction and making technical decisions that shape a team's or domain's long-term trajectory
• Deep expertise in backend programming (e.g., Go, Ruby, Python, or Java) and cloud-native architecture, with proven ability to design highly available, high-throughput systems where correctness is critical
• Track record delivering and scaling financial systems, fund movement platforms, or similarly high-reliability domains where transaction integrity, idempotency, and auditability are core requirements
• Experience leading cross-functional technical initiatives, mentoring engineers, and translating complex distributed systems problems into clear architectural decisions and actionable roadmaps
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality