Technical Product Manager, AI Systems
Summary
Own the AI product strategy for a proactive chat app that handles long-running workflows, multi-step reasoning, and real-world task completion, balancing model capabilities with user needs and system constraints.
About the Role
A1 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.
You define what we build and why, grounded in what AI systems can actually do in production. You sit at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable user value.
This is a hands‑on role for product leaders who are comfortable making decisions under uncertainty and working closely with engineers on hard technical trade‑offs.
What You’ll be Doing
Own the end‑to‑end AI product strategy, grounded in technical feasibility and real‑world constraints.
Translate model capabilities, data limitations, and evaluation results into clear product decisions.
Make hard trade‑offs across quality, latency, cost, reliability, and user experience.
Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration.
Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback.
Drive execution with clear specifications, risk awareness, and disciplined prioritization.
Ensure AI features ship quickly, safely, and reliably into production.
Own AI product quality across UX, correctness, and outcomes.
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.
You define what we build and why, grounded in what AI systems can actually do in production. You sit at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable user value.
This is a hands‑on role for product leaders who are comfortable making decisions under uncertainty and working closely with engineers on hard technical trade‑offs.
What You’ll be Doing
Own the end‑to‑end AI product strategy, grounded in technical feasibility and real‑world constraints.
Translate model capabilities, data limitations, and evaluation results into clear product decisions.
Make hard trade‑offs across quality, latency, cost, reliability, and user experience.
Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration.
Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback.
Drive execution with clear specifications, risk awareness, and disciplined prioritization.
Ensure AI features ship quickly, safely, and reliably into production.
Own AI product quality across UX, correctness, and outcomes.
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.