Cygnify

Technical Product Manager (AI Systems)

Cygnify Singapore, Singapore

Technology, Information and Internet · 11-50 employees

19 h ago
product-manager Senior (5-10 yrs) Full-time Singapore
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About the role

You will define end-to-end AI system requirements and translate model capabilities into clear product decisions. You will also collaborate with engineering teams to ensure systems are reliable, scalable, and aligned with user needs.

What they look for

Technical Product Management AI Systems Machine Learning System Design LLM Data Structures Algorithms Product Strategy Evaluation Frameworks User Experience Data Constraints Model Evaluation Prompt Engineering Pipeline Iteration Feedback Loops Prioritization

Requirements

Candidates must have a strong technical foundation in computer science and hands-on experience with AI-powered products and LLM systems. Proven experience in owning complex technical products and working closely with ML teams is required.

Full description

Technical Product Manager

Role

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.

What You'll be Doing

  • 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

What You Will Need

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

  • Significant experience owning complex, technical products end-to-end.
  • 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.
  • Experience defining evaluation metrics for ML systems.
  • Strong intuition for AI UX patterns and failure handling.
  • Prior experience in zero-to-one product environments.

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.

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