Technical Product Manager

Axe Recruiting; United States; Hybrid; USD 160,000 - 260,000; Full time

Job summary

Axe Recruiting presents a deeply technical product leadership role focused on defining how an AI system should behave, be evaluated and improved. You will work at the intersection of user needs, model capabilities, and engineering support, requiring close collaboration with ML and engineering teams to deliver correct, reliable, and trusted AI-powered experiences.

The role demands hands-on experience with LLM-based products, strong CS fundamentals, and a track record of delivering technical

Qualifications

• Strong computer science fundamentals: algorithms, data structures and system design.
• Solid grasp of modern ML and production behavior of AI systems.
• Ability to read and review technical designs, understand architectures and work deeply with engineers.
• Sharp instincts for model limitations, hallucination, bias, drift, evaluation and failure modes.
• Substantial experience owning complex technical products end-to-end with senior engineers and ML teams.
• Hands-on experience with AI-powered products, especially LLM-based systems, including evaluation, experimentation and feedback loops.
• Ability to turn ambiguous problems into clear, measurable outcomes and executable plans.

Responsibilities

• Write end-to-end requirements for AI capabilities, covering model and system behavior and user experience.
• Translate evaluation results and constraints into clear product decisions.
• Decide trade-offs among quality, cost, latency, safety, reliability and UX.
• Collaborate with ML, backend and client engineers on design, evaluation and iteration.
• Build and refine evaluation framework with offline metrics, online experiments and human feedback.
• Set explicit quality bars and feedback loops for AI-powered experiences.
• Drive delivery with clear specs, prioritization and sound technical judgment.
• Identify failure modes and ensure system predictability and graceful recovery.

Skills

CS fundamentals

ML systems

Architectural reading

Design review with engineers

End-to-end product ownership

Hands-on with LLM-based products

Requirements to outcomes

Decision making under constraints

Job description

A deeply technical product seat: define how the AI system behaves, how it is measured and how it gets better.

The Opportunity

Our client wants a product leader who can read the architecture and challenge the engineers. A well-funded AI applications company, backed by an established technology company in Southeast Asia and building for a global market, they are building an AI-native email application and the agent systems behind it. The role lives at the junction of what users need, what the models can do and what engineering can support. You work directly with ML and engineering to settle how the system should behave, how its quality is judged and how it improves, and you answer for the result: a product that is correct, reliable, useful and trusted.

Role Snapshot

• Location: United States, United Kingdom or Asia (Singapore, South Korea, Indonesia, China)
• Work Model: Hybrid in the US, UK and Seoul for most openings; remote in Singapore, Indonesia and China
• Employment Type: Full-time
• Compensation: Competitive, shared on intro call
• Team: Product, working directly with ML and engineering

What You’ll Own

• Write the end-to-end requirements for AI capabilities, covering model behavior, system behavior and the user experience.
• Turn evaluation results, model capabilities and technical constraints into clear product and system decisions.
• Decide the trade-offs among quality, cost, latency, safety, reliability and UX.
• Join ML, backend and client engineers in system design, evaluation and iteration.
• Build and keep refining the evaluation framework: offline metrics, online experiments and human feedback.
• Set explicit quality bars and feedback loops for every AI-powered experience.
• Drive delivery with clear specs, firm prioritization and sound technical judgment.
• Find the failure modes, and make sure the system behaves predictably and recovers gracefully.

What You Bring

• Strong computer science fundamentals: algorithms, data structures and system design.
• A solid grasp of modern ML and of how AI systems behave once in production.
• Ease reading and reviewing technical designs, understanding architectures and going deep with engineers.
• Sharp instincts for model limitations, hallucination, bias, drift, evaluation and failure modes.
• Substantial experience owning complex technical products end to end, working closely with senior engineers and ML teams.
• Hands-on experience with AI-powered products, LLM-based systems in particular, including model evaluation, experimentation, prompt or pipeline iteration and feedback loops.
• The ability to turn an ambiguous problem into clear requirements, measurable outcomes and a plan that can be executed, weighing ambition against technical and operational reality.
• Good judgment when no answer is obvious, a preference for shipping and experimenting, and the confidence to challenge engineers and researchers constructively in a fast, zero-to-one setting.

Nice to Have

• AI-heavy consumer products you have shipped.
• A past as an engineer or a highly technical product manager.
• Experience defining evaluation metrics for ML systems.
• Good instincts for AI UX patterns and failure handling.
• Earlier experience in zero-to-one product environments.

Why This Role

• Real technical authority: you are expected to understand the system and challenge technical decisions.
• Ownership of how AI quality is defined and measured, not just a feature backlog.
• A small, senior team where product leaders have broad ownership and execute independently.
• A short hiring process: three to four interviews with a quick answer.

Not the Right Fit If

• You manage roadmaps and stakeholders but leave system design to engineering.
• You have not worked hands-on with LLM-based products.
• You need established processes; this is zero-to-one.