Software Engineer, Enterprise Apps

As a Software Engineer on the CX Shared Agent Platforms and SFDC Solutions team, you'll build and extend the platforms that power customer service and compliance operations across Coinbase. This team, part of the Enterprise Applications and Architecture org, owns CX tooling including Salesforce, Maestro QA, and Assembled, enabling agents to resolve customer issues and manage KYC workflows with speed and accuracy. You'll develop full-stack services and integrations that drive agent productivity, support strategic platform transitions, and deliver impact at scale from Brazil.

What you'll do:

• Build and ship backend services using Golang and gRPC that extend CX platform capabilities and support agent workflows across compliance and consumer teams.
• Own the evaluation, integration, and ongoing support of third-party SaaS platforms, ensuring seamless connectivity across the CX tooling ecosystem.
• Partner with product, design, security, and data teams to deliver cross-functional solutions to complex operational and compliance challenges.
• Drive engineering best practices across the team, including code reviews, testing strategies, deployment processes, and observability standards (metrics, logging, tracing).
• Translate complex technical concepts into clear recommendations for non-technical stakeholders across CX, product, and leadership teams.

Required Skills and Experience:

• 5+ years of software engineering experience, with proficiency in Go and hands-on experience building scalable backend services using gRPC, event-driven architectures (Kafka or similar), and SQL or NoSQL databases.
• Demonstrated experience evaluating, integrating, and operating third-party SaaS applications and vendor APIs in a production environment.
• 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.
• Proven ability to contribute to technical architecture decisions and translate them into reliable, high-traffic production systems.
• 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.