Technical Product Manager
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Job Description
Technical Product Manager owning regulated financial-product verticals for BJAK’s Southeast Asian neobank superapp. Shaping systems, AI features, compliance gates, and money-movement reliability.
Responsibilities:
- Own a product vertical end-to-end, including outcomes, metrics, prioritised backlog, and acceptance criteria
- Shape technical design with engineering across system boundaries, money movement, third-party rails, failure handling, security, latency, scalability, and recovery
- Make trade-offs across correctness, speed, cost, reliability, and user experience
- Treat licensing, CDD/KYC, limits, sanctions/PEP screening, transaction monitoring, data residency, and privacy as product inputs
- Apply AI with defined decision boundaries, human oversight, evaluation, and traceability to real records
- Ship feature-complete products behind flags and launch as partner and regulatory gates clear
- Collaborate across Engineering, Design, Compliance, Operations, Treasury, and Finance/Reconciliation
Requirements:
- Significant experience owning a complex technical product end-to-end
- Strong judgement and decisiveness under ambiguity
- Ability to balance product ambition against technical, regulatory, and operational realities
- Ability to work effectively with senior engineers
- Solid system design knowledge, including boundaries, datastores, queues/workflows, APIs, failure modes, and concurrency consistency
- Comfortable reading, reviewing, and challenging design documents
- Able to sketch architectures and sequences; no production coding required
- Experience in a regulated or high-consequence domain such as payments, banking, remittance, or insurance, or demonstrable ability to ramp quickly
- Understanding of money-movement correctness, irreversible states, and third-party partner constraints
- Hands-on experience with LLM-based products
- Ability to define evaluable AI features using offline, online, and human-feedback evaluation
- Realistic understanding of hallucination, drift, data gaps, data-blocked versus model-blocked scenarios, and when models should not be used
- Strong English communication required
- Nice-to-have: engineering or highly technical product management background, zero-to-one experience, AI-heavy consumer product experience, ML/LLM evaluation metrics, AI UX and failure-handling intuition, and Southeast Asia market experience
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