Staff Software Engineer, Customer Administration

Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn’t a place for complacency, it’s a place to be pushed past your perceived limits. If you’re ready to build the future of finance alongside people who refuse to settle for “good enough,” you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase.

Staff Software Engineer, Customer Administration

The Customer Administration Engineering (CAE) team is a core pillar of Coinbase’s Enterprise Applications and Architecture (EAA) org, responsible for building and operating the secure, foundational platforms that power customer data operations across Coinbase. Our flagship product, Control Center, is Coinbase’s secure system of action for internal specialists across CX, Compliance, Legal, Global Investigations, Trust and Risk, and dozens of other teams. It serves approximately 7,000 internal users via its UI and powers a growing ecosystem of internal tools and AI automation via its backend APIs and MCP. We are at an exciting inflection point: evolving Control Center from a human-specialist UI into a modular, AI-agent-ready operations platform. As a Staff Software Engineer, you will be a technical anchor for the CAE team, driving architectural decisions, mentoring engineers, and leading the delivery of high-impact, cross-cutting platform capabilities.

What You’ll Do

• Architect and deliver foundational platform capabilities including MCP tool registries, AI orchestration layers, risk-based access automation, and the away-team contribution model that enables product groups across Coinbase to build on the platform safely and at speed
• Drive the evolution of Control Center into an AI-agent-ready, headless operations platform, designing and implementing MCP procedure constructs, agentic guardrails, HITL orchestration, and evaluation frameworks that enable both human and autonomous AI agents to execute sensitive customer operations securely
• Partner with the Engineering Manager and Product counterparts to define architectural roadmaps, author TDDs, lead design reviews, decompose complex initiatives into deliverable milestones, and raise the engineering quality bar through code review and mentorship
• Build and maintain highly reliable, secure, distributed backend services, owning SLO definitions, observability instrumentation, incident response, and operational readiness for Tier-1 platform systems
• Collaborate across EAA engineering teams, Product Engineering, and Security Engineering to deliver cross-functional outcomes and drive shared platform primitives that eliminate duplicated infrastructure across the portfolio

Required Skills and Experience

• 8+ years of hands-on software engineering experience, with a demonstrated track record of architecting and delivering large-scale, high-traffic distributed systems in production, including deep proficiency in backend service design, API development (gRPC, MCP, GraphQL), and scalable microservices architectures
• Proven ability to independently lead ambiguous, high-impact technical initiatives from whiteboard to production, writing high-quality, well-tested code and setting the standard for others across complex, multi-team problem spaces
• Strong experience with cloud-native infrastructure and the modern backend stack: AWS, Kubernetes, Terraform, BuildKite/CircleCI, event-driven architectures (Kafka, MQ), distributed caching (Redis/Memcached), and proficiency in SQL and/or NoSQL databases
• Track record of building secure, compliant internal tools or platforms, with deep appreciation for security controls, access management, audit logging, data governance, and engineering rigor in a regulated financial services environment
• Experience building or integrating with agentic AI systems, including MCP servers, LLM orchestration layers, RAG pipelines, HITL workflows, or evaluation and guardrail frameworks for production agentic workloads
• Proficiency in Go (Golang) as a primary backend language, with willingness to work across Python where applicable in the evolving AI stack
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficien…