Staff Software Engineer, Core AI Infrastructure

Coinbase is a company committed to increasing economic freedom, and they are seeking a Staff Software Engineer for their Core AI Infrastructure team. The role involves building and maintaining critical AI infrastructure, ensuring reliability and automation, and collaborating with various teams to enhance platform capabilities.

Responsibilities:

• Own end-to-end delivery of AI products by building production-grade distributed systems, including serving infrastructure, data pipelines, and deployment orchestration across the full stack throughout the SDLC
• Drive platform adoption by designing clean APIs, abstractions, and developer-facing tooling that enable product teams to integrate AI capabilities without bespoke infrastructure requests
• Partner with engineering and product leadership across Platform and other product groups to align infrastructure requirements, resolve cross-team technical dependencies, and define shared platform contracts
• Shape engineering standards and technical culture by establishing architectural patterns, mentoring engineers, and raising the bar on code quality, observability, and operational excellence
• Build full-stack applications that power internal AI products and infrastructure using Go or Python

Requirements:

• 8+ years of experience automating and supporting cloud infrastructure (AWS) and network environments, with hands-on use of infrastructure-as-code tools such as Terraform, Ansible, Chef, Puppet, or Salt
• Proven experience deploying, managing, and troubleshooting containerized workloads using Docker and Kubernetes in production environments
• Proficiency in at least one programming language (Python, Bash, Ruby, or Go) and version control workflows using Git-based CI/CD pipelines
• Platform-builder mindset with proven history of designing reusable infrastructure, APIs, and abstractions adopted by multiple teams across an engineering organization
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality