What you'll be doing: - Own a vertical end-to-end — define outcomes and metrics, maintain a value/risk/dependency-driven backlog, and establish crisp acceptance criteria. - Shape the technical design with engineering — system boundaries, money-movement correctness, third-party rail reliance, failure/retry/refund paths, security, latency, scalability, and recovery. - Make hard trade-offs across correctness, speed, cost, reliability, and UX—and defend them to engineering, compliance, or operations leads. - Treat regulated constraints as first-class inputs—licensing scope, CDD/KYC and limits, sanctions/PEP screening, transaction monitoring, data residency and privacy; identify launch gates versus forward-readiness. - Apply AI where it earns its place—define what it can decide, when a human stays in the loop, how it’s evaluated, and what it does when unsure; every AI-surfaced number traces to a real record. -

What you'll be doing: - Own a vertical end-to-end — define outcomes and metrics, maintain a value/risk/dependency-driven backlog, and establish crisp acceptance criteria. - Shape the technical design with engineering — system boundaries, money-movement correctness, third-party rail reliance, failure/retry/refund paths, security, latency, scalability, and recovery. - Make hard trade-offs across correctness, speed, cost, reliability, and UX—and defend them to engineering, compliance, or operations leads. - Treat regulated constraints as first-class inputs—licensing scope, CDD/KYC and limits, sanctions/PEP screening, transaction monitoring, data residency and privacy; identify launch gates versus forward-readiness. - Apply AI where it earns its place—define what it can decide, when a human stays in the loop, how it’s evaluated, and what it does when unsure; every AI-surfaced number traces to a real record. -