Remote-First Staff Software Engineer, AI Platform

Coinbase, Inc.; Washington (District of Columbia); Hybrid; USD 218,000 - 257,000; Full time

Job summary

Coinbase, Inc. is seeking a Staff Software Engineer in the Enterprise Applications and Architecture group. You will anchor across eight globally distributed squads, shaping AI maturity and developer experience while driving reliability and security for Tier-1 systems.

The role emphasizes architecture, platform excellence, and cross-team collaboration. You will work on agentic AI integrations, Go and Python, and cloud-native stacks, with emphasis on measurable improvements in workflow efficiency

Qualifications

• 8+ years of software engineering with distributed systems.
• Lead high-impact technical initiatives across multi-team spaces.
• Cloud-native infra with AWS, Kubernetes and CI/CD.
• Secure internal tools and data governance in regulated environments.
• Agentic AI systems with Go and Python proficiency.

Responsibilities

• Own AI maturity and developer-experience roadmap with squads.
• Lead platform excellence to improve reliability and observability.
• Define build-versus-buy strategy for AI tooling.
• Provide architectural coverage across squads with coherence.
• Build reliable backend services with SLO ownership and security.

Skills

Backend architecture

API development

Microservices

Cloud-native

AWS

Kubernetes

Terraform

CI/CD

Kafka

NoSQL databases

Security governance

Agentic AI systems

Go

Python

Generative AI governance

Tools

GraphQL

gRPC

Job description

Coinbase, Inc. is seeking a Staff Software Engineer in the Enterprise Applications and Architecture group. You will anchor across eight globally distributed squads, shaping AI maturity and developer experience while driving reliability and security for Tier-1 systems.

The role emphasizes architecture, platform excellence, and cross-team collaboration. You will work on agentic AI integrations, Go and Python, and cloud-native stacks, with emphasis on measurable improvements in workflow efficiency