Software Engineer, Enterprise Apps

Coinbase is a remote-first company focused on increasing economic freedom. As a Software Engineer for Enterprise Apps, you will build platforms and services that enhance customer experience workflows for support agents, owning full-stack development and shipping features that improve agent productivity and customer satisfaction.

Responsibilities:

• Build and ship full-stack services and applications using Golang, gRPC, TypeScript, and React to support CX agent workflows and automation
• Own the design and implementation of third-party platform integrations that extend the capabilities of Coinbase's internal CX tooling
• Partner with team members on architecture decisions, code reviews, and engineering best practices across testing, deployment, and observability
• Identify and mitigate technical risks during design and implementation to maintain platform reliability for high-traffic, production systems
• Translate complex technical concepts into clear narratives for non-technical stakeholders across CX, product, and leadership teams

Requirements:

• 3+ years of software engineering experience, including 3+ years building and shipping user-facing web applications with JavaScript and modern component-based frameworks (React)
• Proficiency in Go, with hands-on experience building scalable backend services using gRPC, event-driven architectures (Kafka or similar), and SQL or NoSQL databases
• Experience operating production systems on AWS with Kubernetes, Terraform, and CI/CD tooling (BuildKite or similar), including implementation of rate limiters, caching, load balancing, and circuit breakers
• Demonstrated experience integrating with third-party vendor APIs and SaaS platforms in a production environment
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality
• Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality