The opportunity
Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom.
What you'll do
Own the EAA-CX AI maturity and developer-experience roadmap in partnership: with engineering leadership, embedding with squads to surface opportunities, prototyping on Coinbase's existing AI platform, and driving adoption through working demos and feedback loops.
Lead platform excellence workstreams that improve reliability, observability,: change-failure rate, and operational readiness for Tier-1 systems, partnering with engineering managers to ensure practices persist on the teams.
Define build-versus-buy strategy for developer-experience and AI tooling: across EAA-CX, evaluating what to build internally, adopt from partner teams, procure from vendors, or retire.
Provide Staff-level architectural coverage across squads facing complex: challenges, ramping in to land architecture or delivery and ramping off while maintaining portfolio-wide coherence.
Build highly reliable, secure distributed backend services with full SLO: ownership, observability, and incident response, ensuring automated outputs and production changes are traceable, reviewable, and safe in a regulated environment.
+ years of software engineering experience with a demonstrated track record: architecting and delivering large-scale distributed systems, including deep proficiency in backend service design, API development (gRPC, MCP, GraphQL), and scalable microservices architectures.
What they're looking for
- Proven ability to independently lead ambiguous, high-impact technical: initiatives from whiteboard to production across multi-team problem spaces, writing high-quality, well-tested code that sets the standard for others.
- Strong experience with cloud-native infrastructure including AWS, Kubernetes,: Terraform, CI/CD pipelines, event-driven architectures (Kafka, MQ), distributed caching, and SQL or NoSQL databases.
- Track record building secure, compliant internal tools or platforms with deep: appreciation for security controls, access management, audit logging, and data governance in a regulated environment.
- Experience building or integrating with agentic AI systems including MCP: servers, LLM orchestration layers, RAG pipelines, HITL workflows, or evaluation and guardrail frameworks, with proficiency in Go and willingness to work across Python.
