Overview
Own the strategy, design, evaluation, and reliability of AI-agent products. Partner closely with engineering and ML teams to turn model capabilities into predictable, trusted user experiences.
What you'll do
- Define end-to-end AI system requirements from capabilities through user impact.
- Translate model capabilities, data constraints, and evaluation results into product decisions.
- Balance quality, latency, cost, reliability, and user experience trade-offs.
- Partner with ML, backend, and mobile engineers on system design and iteration.
- Define evaluation frameworks using offline metrics, online experiments, and human feedback.
- Drive execution through specifications, prioritization, and feedback loops.
- Own product quality, including correctness, predictability, and user trust.
What you'll need
- Strong computer science fundamentals in algorithms, data structures, and system design.
- Solid understanding of machine learning fundamentals and production AI systems.
- Experience with AI-powered products, including LLM-based systems.
- Experience with model evaluation, prompt or pipeline iteration, and feedback loops.
- Understanding of model limitations, hallucinations, bias, and drift.
- Significant experience owning complex technical products end-to-end.
- Ability to work closely with senior engineers and ML teams in ambiguous environments.
Nice to have
- Experience shipping AI-heavy consumer products.
- Engineering or highly technical product management background.
- Experience defining evaluation metrics for ML systems.
- Understanding of AI UX patterns and failure handling.
- Experience in zero-to-one product environments.
Details
- Location: United States.
- Interviews may be conducted virtually or onsite.
Read the full description and apply on the company’s own careers page.
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