Remote-First Staff Software Engineer, AI Platform & DX

Coinbase, Inc.; Cheyenne (WY); Remote; USD 218,000 - 257,000; Full time

Job summary

Coinbase is seeking a Staff Software Engineer to lead AI maturity and developer-experience efforts across the Customer Experience engineering squads. You will architect scalable backend services on Coinbase's AI platform, improve reliability and observability, and guide build-versus-buy decisions for AI tooling.

You will collaborate with engineering leadership to deliver high-impact, secure, compliant, and production-ready systems across global teams, using Go and Python, on AWS and Kubernetes.

Qualifications

• 8+ years of software engineering with distributed systems experience.
• Backend service design and API development with modern stacks.
• Experience with cloud-native infrastructure (AWS, Kubernetes).
• Security controls and data governance in regulated environments.
• Experience with agentic AI systems and AI tooling.

Responsibilities

• Own AI maturity and developer-experience roadmap across CX engineering squads.
• Lead platform excellence to improve reliability and observability.
• Define build-versus-buy strategy for AI tooling and developer experience.
• Provide staff-level architectural coverage across squads.
• Build and maintain reliable distributed backend services with SLOs.

Skills

Distributed systems design

Backend API development

Go

Python

AWS

Kubernetes

Terraform

CI/CD pipelines

Security & compliance

Agentic AI systems

GRPC

GraphQL

Kafka

NoSQL databases

SQL databases

Tools

Kafka

MQ

SQL databases

NoSQL databases

Job description

Coinbase is seeking a Staff Software Engineer to lead AI maturity and developer-experience efforts across the Customer Experience engineering squads. You will architect scalable backend services on Coinbase's AI platform, improve reliability and observability, and guide build-versus-buy decisions for AI tooling.

You will collaborate with engineering leadership to deliver high-impact, secure, compliant, and production-ready systems across global teams, using Go and Python, on AWS and Kubernetes.