Technical Product Manager

Pivot Search; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Pivot Search is seeking a deeply technical product leader to shape an AI-powered chat app focused on reliable, real-world task completion. You will work with engineers to define system design, evaluation, and trade-offs across capabilities, latency, and UX.

You will translate model capabilities and data constraints into clear product decisions, balancing ambition with operational reality while guiding global user interactions and maintaining trust.

Qualifications

• Solid CS fundamentals and system design knowledge.
• Strong ML fundamentals and production AI exposure.
• Ability to read and discuss technical design documents.

Responsibilities

• Define end-to-end AI system requirements from capability to user impact.
• Translate model capabilities and data constraints into decisions.
• Make trade-offs across quality, latency, cost, reliability, and UX.
• Collaborate with ML, backend, and mobile engineers on design, evaluation and iteration.
• Define evaluation frameworks across offline metrics, online experiments, and human feedback.
• Drive execution with clear specs, strong judgment, and disciplined prioritization.
• Ensure systems ship quickly, safely, and reliably, with strong feedback loops.
• Own product quality end-to-end - correctness, predictability, and user trust.

Skills

CS fundamentals

Algorithms

System design

ML fundamentals

Production AI

Model evaluation

Prompt engineering

Data analysis

Job description

Our client is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.

This is a deeply technical, hands-on role. Work directly with engineers on system design, evaluation, and trade-offs-defining requirements, but shaping how the system works for global users. You work at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable behavior in a real-world application.

Key Responsibilities

• Research and define end-to-end AI system requirements from capability to behavior to user impact
• Translate model capabilities, data constraints, and evaluation results into clear product and system decisions
• Make hard trade-offs across quality, latency, cost, reliability, and UX
• Work closely with ML, backend, and mobile engineers on system design, evaluation, and iteration
• Define and evolve evaluation frameworks across offline metrics, online experiments, and human feedback
• Drive execution with clear specs, strong judgment, and disciplined prioritization
• Ensure systems ship quickly, safely, and reliably, with strong feedback loops
• Own product quality end-to-end - correctness, predictability, and user trust

Skills & Experience

Technical foundation

• Strong grounding in computer science fundamentals, including algorithms, data structures, and system design.
• Solid understanding of ML fundamentals and how modern AI systems behave in production.
• Comfort reading, reviewing, and discussing technical design documents.

AI & ML experience

• Hands-on exposure to AI-powered products, including LLM-based systems.
• Experience working with model evaluation, prompt or pipeline iteration, and feedback loops.
• Strong intuition for model limitations, hallucinations, bias, and drift.

Product leadership

• Proven ability to work closely with senior engineers and ML teams.
• Strong judgment and decision-making ability in ambiguous, fast-moving environments.
• Ability to balance ambition with technical and operational reality.

Nice to have

• Experience shipping AI-heavy consumer products.
• Background as an engineer or highly technical product manager.
• Strong intuition for AI UX patterns and failure handling.

Outcomes

• Product strategy clearly aligns AI capabilities with user needs and company priorities.
• AI features deliver real value, are understandable, predictable, and trusted by users.
• Decisions balance quality, speed, cost, and reliability effectively under uncertainty.
• Roadmaps and priorities are clear, with fast iteration based on real user feedback.
• Teams are aligned, focused, and able to execute on AI product goals with minimal friction.