Staff Software Engineer, Core Reliability

As a Staff Software Engineer, Core Reliability on the Infra Reliability team within Platform, you'll help Coinbase scale 50x by improving reliability, security, and deployment safety across our production environment. This team owns the systems that secure service configurations and secrets, reduce customer-facing incidents, and strengthen deployment infrastructure supporting thousands of services and hundreds of daily releases. You'll lead high-impact reliability projects that make our entire service environment more resilient and safer for customers.

What you'll do:

• Own the design and delivery of reliability projects and features that improve resiliency across Coinbase's service environment in partnership with other engineering teams.
• Partner with critical T0/T1 services to understand architecture, improve scalability, and reduce operational toil.
• Build and enhance systems that securely manage service configurations and secrets at scale.
• Improve canary-based release systems and expand deployment capabilities to support thousands of services and hundreds of daily deployments with fewer incidents.
• Drive reliability best practices and strengthen reliability culture across engineering teams at Coinbase.

Required Skills and Experience:

• 10+ years of software engineering experience designing, building, and maintaining production services in service-oriented architectures, including experience with Ruby, Go, Terraform, and cloud platforms (AWS, GCP or Azure).
• Demonstrated ability to design and operate reliable, high-throughput, low-latency distributed systems at scale, with a track record of writing well-tested, production-quality code.
• Proven experience with observability and monitoring tools (e.g., Kibana, Datadog) to debug complex production issues, tune system performance, and reduce incident frequency.
• Experience writing and verbally communicating architecture decisions to cross-functional engineering stakeholders.
• Ability to participate in on-call rotations and respond to issues outside normal business hours.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.