Senior Site Reliability Engineer, AI Transformation

You'll join a high-performing team of engineers driving AI transformation at Coinbase as a Senior Site Reliability Engineer on the IT Operations team. This team builds and scales the infrastructure powering Coinbase's AI products, with direct exposure to senior leadership in a fast-paced, incubator-style environment. You'll own the reliability and automation of critical AI infrastructure, ensuring our systems are resilient, observable, and secure at scale.

What you'll do:

• Own the reliability, monitoring, and incident response lifecycle for AI infrastructure services, including on-call support for AWS deployment pipelines, root cause analysis, and blameless retros.
• Build automation and tooling to streamline operational IT workflows, eliminate manual tasks, and improve deployment velocity across CI/CD frameworks and Kubernetes environments.
• Partner with the Coinbase Infrastructure team to extend CI/CD frameworks supporting IT services and enterprise network platforms, and with Security and Compliance to integrate surveillance tooling into deployment pipelines.
• Strengthen observability and documentation standards across IT engineering by defining metrics, implementing monitoring solutions, and maintaining technical documentation that sets a standard of excellence.
• Develop full-stack applications that power internal AI products and infrastructure with Go or Python.

Required Skills and Experience:

• 5+ years of experience automating and supporting cloud infrastructure (AWS) and network environments, with hands-on use of infrastructure-as-code tools (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 scripting or programming language (Python, Bash, Ruby, or Go) and version control workflows using Git-based CI/CD pipelines.
• Track record of leading incident response in environments with strict SLAs, including root cause analysis, blameless retros, and measurable reliability improvements.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.