Technical Product Manager

About the role

In this deeply technical, hands‑on role, you will work directly with engineers on system design, evaluation, and trade‑offs—defining requirements and shaping how the system works for global users. You will operate at the intersection of user needs, model capability, and system constraints, turning AI potential into 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 user experience.
• 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 specifications, strong judgment, and disciplined prioritization.
• Ensure systems ship quickly, safely, and reliably, with strong feedback loops.
• Own product quality end‑to‑end, including correctness, predictability, and user trust.

Required profile

• Strong grounding in Computer Science fundamentals, including algorithms, data structures, and system design.
• Solid understanding of Machine Learning fundamentals and production AI behavior.
• Comfortable reading, reviewing, and discussing technical design documents.
• Hands‑on exposure to AI‑powered products, especially LLM‑based systems.
• Experience with model evaluation, prompt or pipeline iteration, and feedback loops.
• Strong intuition for model limitations, hallucinations, bias, and drift.
• Significant experience owning complex, technical products end‑to‑end.
• Proven ability to collaborate closely with senior engineers and ML teams.
• Strong judgment and decision‑making ability in ambiguous, fast‑moving environments.
• Able to balance ambition with technical and operational reality.

Required skills

• Algorithms
• Data structures
• System design
• Machine Learning
• Large Language Models