Product Manager

🔥 19 minutes ago

🌐 Singapore, China, +1 more countries – Remote

🇸🇬 Singapore – Remote 🇨🇳 China – Remote 🇲🇾 Malaysia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

✅ Product Manager

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Hupo

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🛡️ Insurance

Artificial Intelligence • SaaS • Insurance

Hupo is an AI-first company (founded in 2022) that builds a full-stack, software platform to coach and upskill frontline financial advisors and insurance distributors. Using AI to restore confidence, accelerate learning, and improve sales performance, Hupo targets Wealth & Insurance distribution and sells enterprise-grade coaching and productivity tools designed to reduce early rep churn and accelerate mastery. The company emphasizes remote, high-autonomy culture and positions its product as an AI-powered engine for enterprise clients in financial services and insurance distribution.

📋 Description

• Take agentic automations from concept to a product line • Own roadmap, prioritisation, OKRs, and outcomes for lead categorization and scoring, lead-to-advisor matching, and renewal and cross-engagement opportunity detection • Define the governance harness for agentic AI, including autonomy boundaries, human-in-the-loop requirements, audit trails, and evaluation gates • Work with compliance and engineering leadership on AI governance • Design autonomous capabilities within regulatory constraints for banking and insurance clients • Define automation capabilities and collaborate with peer product management and platform engineering on shared infrastructure • Understand enterprise BFSI distribution workflows, agency structures, and compliance constraints and translate them into products • Lead a squad of engineers and a designer to ship and iterate quickly while maintaining safety and evaluation standards • Use AI tooling to increase productivity • Use data to measure match quality, opportunity-detection precision, advisor adoption, and downstream conversion • Establish priorities, outcomes, success measures, and foundations for evaluating and governing agentic capabilities • Continuously improve automation quality and impact using data and customer outcomes

🎯 Requirements

• Built and shipped LLM-powered decisioning or automation systems in practice, including tool use, orchestration, structured outputs, and evaluation design • Built evaluation harnesses, guardrails, human review workflows, and audit evidence for trustworthy AI decisions • Sound judgment about autonomy in high-stakes settings; able to determine when AI should act, recommend, or hand off to a human and defend that reasoning to compliance officers • Fluency with prompting, retrieval, and evaluation • Uses AI tooling by default and can demonstrate it • Thrives in ambiguity and takes ownership independently • Communicates clearly and concisely in writing and in person across technical, commercial, and compliance audiences • Deep domain knowledge in insurance, wealth management, or financial services sales and servicing (nice-to-have) • Enterprise SaaS experience, especially deploying into large regulated institutions (nice-to-have) • Experience with lead management, CRM intelligence, sales operations tooling, or recommendation and matching systems (nice-to-have) • Familiarity with AI governance frameworks in financial services, such as MAS FEAT or HKMA GenAI guidance (nice-to-have)