Own core developer infrastructure platforms, including CI/build systems and deployment orchestration, across the full lifecycle from design through production operation.
Own end-to-end delivery of AI products by building production-grade distributed systems, including serving infrastructure, data pipelines, and deployment orchestration across the full stack throughout the SDLC.
Own the design, development, and automation of routing infrastructure that directs application traffic to Kubernetes backends at scale. Build capabilities on top of Envoy-based reverse proxies, Istio gateways, Ambient mesh, and SPIFFE service authentication.
Own the technical architecture of Transfers' fund movement systems, driving design decisions on distributed system structure, correctness guarantees, and scalability across crypto and fiat rails.
Own backend services powering Coinbase Advisor and Strategies, from technical design through launch and ongoing operation. Build integrations with Coinbase's trading APIs so agent recommendations and user-configured strategies translate into correct, auditable execution.
Own the EAA-CX AI maturity and developer-experience roadmap in partnership with engineering leadership, embedding with squads to surface opportunities, prototyping on Coinbase's existing AI platform, and driving adoption through working demos and feedback loops.
Own the full IDV ML stack, including document authenticity models, 1:1 and 1:N face-match, liveness detection, presentation-attack detection, and deepfake/injection detection from feature pipeline through threshold tuning and production enforcement.
Architect and build production Agentic AI systems for compliance automation, including LLM-powered agents, orchestration pipelines, and decision support workflows that replace manual compliance processes.
Own the design and delivery of production ML systems, applying LLMs, deep learning, graph neural networks, and classical ML techniques to solve complex customer experience problems.
Embed with FP&A and Treasury leadership to surface the automation opportunities with the greatest business leverage — developing ground-level understanding of workflows like period-end close, variance analysis, and liquidity stress-testing before writing a single line of code.
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