Senior Product Manager (AI & Agri-Tech Operations)

Role Overview

• Team structure: You'll work in squads with product managers, engineers, and designers
• Location: Based in Ho Chi Minh City (Vietnam) or Jakarta/Java Island (Indonesia)
• Language requirements: Fluency in English is essential; fluency in Vietnamese or Bahasa Indonesia is expected
• Reporting: Directly to Chief Product Officer
• Work style: Fully remote with regular field visits
• Field work: You'll visit farmers, communities, and stakeholders. Expect to get your hands dirty in rice paddy fields, install technologies, and build close relationships with farming communities

What you will own (Responsibilities)

1) Product strategy + business outcomes

• Define the product strategy for a major Rize product area (platform + ops), aligned to business goals.
• Translate company strategy into an execution plan: clear bets, sequencing, and tradeoffs.
• Own the unit economics and financial impact of your product area (revenue, cost-to-serve, loss rates, throughput) as it grows toward P&L accountability.

2) End-to-end delivery leadership

• Drive discovery, prioritization, roadmap, and execution with Engineering + Design.
• Write crisp problem statements, requirements, and acceptance criteria.
• Run stakeholder reviews with speed: push decisions to closure, manage risk, and unblock teams.

3) Stakeholder alignment + decision-making

• Bring together Operations, Country teams, Finance, MRV, and Engineering to align on goals and constraints.
• Operate as the “decision integrator” — when inputs conflict, synthesize them into a single recommended path.
• Communicate with extreme clarity: narratives, memos, async updates, and structured meeting outcomes.

4) AI-enabled product management (not buzzwords)

We want someone who has already used AI to produce real leverage — and can do it again inside our product and our workflows.

You will:

• Use AI tools to accelerate research, PRDs, analysis, and iteration speed.
• Design AI-assisted workflows and agent behavior (scheduling, exception surfacing, data suggestions).
• Define what “good” looks like: evaluation, monitoring, feedback loops, and human override patterns.

5) Remote sensing & satellite-first product thinking

• Identify where satellite-derived signals (e.g., planting/harvest timing, anomalies) can reduce field workload, improve decision quality, and tighten verification loops.
• Partner with data/RS teams to translate satellite outputs into product surfaces: alerts, planning views, risk scores, and exception queues.

6) Data + analytics rigor

• Define leading/lagging indicators and instrumentation for every major release.
• Partner with analytics to translate platform events into a product insight loop.
• Use data to settle debates, not opinions.