BJAK is building a Neobank Superapp for Southeast Asia. As a Technical Product Manager, you will own a vertical end-to-end product area—such as payments and expense management, remittance, insurance, or wealth and trading—from strategy and outcomes to roadmap and the technical design and delivery of the systems behind it. This is a money-movement product where licensing, compliance, and third-party rails are core constraints. We are AI-native by default, focusing on where models genuinely improve outcomes while maintaining deterministic systems that are reliable, auditable and trusted when money is involved. What you'll be doing: Own a vertical end-to-end — define outcomes and metrics, maintain a backlog prioritized by value, risk, dependency, and strategic priority, and specify acceptance criteria. Shape the technical design with engineering—system boundaries, money-movement correctness (idempotency, ledgering, reconciliation), third-party rail reliance and rail-down behavior, 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 product inputs—licensing scope, CDD/KYC and limits, sanctions/PEP screening, transaction monitoring, data residency and privacy. Know which are hard launch gates and which are forward-readiness. Apply AI where it earns its place—define what it's allowed to decide, where a human stays in the loop, how it's evaluated, and what it does when unsure. Every

BJAK is building a Neobank Superapp for Southeast Asia. As a Technical Product Manager, you will own a vertical end-to-end product area—such as payments and expense management, remittance, insurance, or wealth and trading—from strategy and outcomes to roadmap and the technical design and delivery of the systems behind it. This is a money-movement product where licensing, compliance, and third-party rails are core constraints. We are AI-native by default, focusing on where models genuinely improve outcomes while maintaining deterministic systems that are reliable, auditable and trusted when money is involved. What you'll be doing: Own a vertical end-to-end — define outcomes and metrics, maintain a backlog prioritized by value, risk, dependency, and strategic priority, and specify acceptance criteria. Shape the technical design with engineering—system boundaries, money-movement correctness (idempotency, ledgering, reconciliation), third-party rail reliance and rail-down behavior, 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 product inputs—licensing scope, CDD/KYC and limits, sanctions/PEP screening, transaction monitoring, data residency and privacy. Know which are hard launch gates and which are forward-readiness. Apply AI where it earns its place—define what it's allowed to decide, where a human stays in the loop, how it's evaluated, and what it does when unsure. Every