Senior Software Engineer, Backend

What you’ll be doing

• Own the design and delivery of agentic AI systems that power Coinbase's customer support and compliance automation, from LLM orchestration through production deployment and monitoring.
• Build scalable, secure backend infrastructure in Python and Golang that serves AI workloads, including model integration pipelines, guardrails, grounding mechanisms, and measurement frameworks.
• Drive end-to-end project execution on complex AI initiatives, making technical trade-offs across latency, accuracy, cost, and reliability.
• Partner with Customer Experience, Compliance, and product engineering teams to identify high-impact automation opportunities and translate operational pain points into AI-powered solutions.
• Strengthen engineering quality across the team by leading code reviews, mentoring engineers on AI system design patterns, and contributing to on-call rotations and incident response.

What we look for in you

• 5+ years of experience in software engineering, with proven expertise in designing, building, and maintaining production services using a microservices architecture.
• Hands-on experience building LLM-based applications or AI/ML systems in production, including prompt engineering, retrieval-augmented generation (RAG), or agentic AI frameworks.
• Proficiency in Python and Golang (or comparable backend languages), with experience integrating third-party AI models and APIs into production workflows.
• Track record of delivering end-to-end projects with measurable business impact in ambiguous problem spaces.
• Experience building data pipelines, integrating with external vendors, or working with large-scale unstructured data sources (e.g., blockchain data, customer interaction logs).
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Nice to haves

• Experience navigating rapid company growth (e.g., from startup to mid-size).
• Familiarity with GenAI frameworks/tools, Python, GoLang, Docker, Postgres, MongoDB.
• Background in AI/LLM infrastructure is a strong plus.