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
Architect multi-agent systems using advanced orchestration frameworks: (LangGraph, Google ADK) to automate complex customer support procedures end-to-end.
Build and scale integrations using Model Context Protocol (MCP) to connect: LLMs with internal Coinbase APIs, databases, and third-party tooling.
Develop automated "LLM-as-a-judge" evaluation pipelines to monitor, measure,: and improve the performance of non-deterministic AI agents in production.
Implement RAG, fine-tuning, and prompt engineering techniques to ensure: chatbot responses are grounded, accurate, and compliant with Coinbase policies.
Ship production-ready Python services that are resilient, low-latency, and: capable of handling Coinbase-scale traffic across asynchronous microservices.
Partner with Conversation Design and Product to translate complex business: logic into executable agent procedures within the decentralized architecture.
What they're looking for
- + years building and scaling ML/AI systems in production, with demonstrated: experience implementing agentic "Loop" or "ReAct" based systems where AI takes actions autonomously.
- Deep understanding of the LLM lifecycle including context window management,: token optimization, structured output parsing (Pydantic, JSON mode), and multi-agent orchestration frameworks (LangGraph, Google ADK, or similar).
- Strong proficiency in Python with hands-on experience in microservices: architecture, asynchronous programming, high-throughput APIs, and vector databases (Pinecone, Weaviate, or equivalent).
- Demonstrated ability to explain model behaviors and technical trade-offs to: non-technical stakeholders across CX, Legal, and Product teams.
