AI Product Manager

Location: Remote, Indonesia

Company

Building a proactive smart assistant that brings AI intelligence to conversations, errands, organization, and everyday workflows.

What you will do

• Define end-to-end AI system requirements from model capabilities through user behavior and impact.
• Translate model capabilities, data constraints, and evaluation results into product and system decisions.
• Make trade-offs across quality, latency, cost, reliability, and user experience.
• Collaborate with ML, backend, and mobile engineers on system design, evaluation, and iteration.
• Define evaluation frameworks spanning offline metrics, online experiments, and human feedback.
• Drive execution through clear specifications, prioritization, feedback loops, and end-to-end ownership of product quality.

Requirements

• Strong computer science fundamentals, including algorithms, data structures, and system design.
• Solid understanding of ML fundamentals and how modern AI systems behave in production.
• Hands-on experience with AI-powered products, including LLM-based systems.
• Experience with model evaluation, prompt or pipeline iteration, and feedback loops.
• Significant experience owning complex technical products end to end and collaborating closely with senior engineers and ML teams.
• Strong judgment in ambiguous, fast-moving environments, with the ability to balance ambition against technical and operational constraints.

Nice to have

• Experience shipping AI-heavy consumer products.
• Engineering background or experience as a highly technical product manager.
• Experience defining evaluation metrics for ML systems.
• Strong intuition for AI UX patterns and failure handling.
• Experience in zero-to-one product environments.

Culture & Benefits

• Remote work based in Indonesia.
• Small, high-talent-density, hands-on team.
• Collective decision-making and rapid execution.
• Focus on balancing high-quality delivery with fast learning and iteration.
• Virtual and/or onsite interviews with a prompt hiring decision.

Hiring process

• Three to four interviews are scheduled when there appears to be a fit.
• Applications are evaluated by technical team members.
• Interviews are conducted via virtual meetings and/or onsite.