Technical Product Manager, AI Systems
- Role
- Product
- Employment
- Full-time
Open to US only. Set where you work from to check your eligibility.
No BS summary
Technical Product Manager for AI systems. Requires strong CS fundamentals, ML understanding, and hands-on experience with AI products, LLMs, and model evaluation. Must have proven product leadership experience with complex technical products and ability to collaborate with engineers and ML teams.
Core skills
Required skills
Optional skills
ABOUT A1
There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.
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. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time.
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.
HOW WE WORK
The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning.
Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product.
INTERVIEW PROCESS
If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.
Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.
We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.
What you'll do
- 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 they require
- 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.
- 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.
- 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.
Benefits
- 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.
An AI product team building the next generation of intelligent productivity applications, focused on long-running AI workflows that manage conversations, coordinate actions, maintain context, and interact with external services with minimal user input.