AI Principal Product Manager

United StatesRemoteFull-timelead

Product ManagementPrincipal Product Manager

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Requirements Summary

8+ years of product management experience in consumer products at scale, including recent hands-on experience shipping LLM-powered products such as assistants, agents, or copilots to real users.

Technical Tools

Product ManagementPrincipal Product Manager

As an AI Principal Product Manager, you will define and launch a new AI-powered consumer product from zero to one, transforming a complex planning experience into something more intuitive and personalized. You’ll operate with significant autonomy, owning product strategy, roadmap, experimentation, and measurable outcomes from concept through launch. The role combines deep product leadership with hands-on fluency in LLMs, agentic systems, AI evaluation, and production economics. You’ll turn proprietary data, user insights, and domain expertise into differentiated experiences that general-purpose AI cannot easily replicate. Success will require balancing innovation with trust, user control, measurable value, and sustainable unit economics. You’ll also serve as a senior thought partner across product, engineering, design, marketing, and data science as AI capabilities continue to evolve.

Own the product lifecycle from strategy and rapid prototyping through early user cohorts, iteration, launch, and ongoing optimization.
Define the product vision, target audience, positioning, distribution strategy, category narrative, and long-term business opportunity in partnership with Product Marketing.
Establish a clear product philosophy for trustworthy AI, determining when an AI experience should guide, ask questions, or take action while ensuring users remain in control.
Run rapid build-measure-learn cycles, prototyping frequently, testing concepts with users and experts, and quickly discontinuing approaches that lack supporting evidence.
Define product success metrics, instrumentation, and unit economics, including understanding and managing the cost of serving AI-powered experiences.
Translate proprietary user, vendor, behavioral, review, and planning data into differentiated AI-powered product experiences.
Make informed tradeoffs across models, context, memory, tools, caching, performance, and cost to create effective production AI experiences.
Partner with product, engineering, design, marketing, and data science leadership to shape broader AI strategy and identify opportunities for new product capabilities.
Build compelling product narratives that align executives and cross-functional teams around ambiguous and emerging problem spaces.
Continuously use user feedback, experimentation, and performance data to refine the product roadmap and improve outcomes.

Requirements

~2 min read

8+ years of product management experience in consumer products at scale, including recent hands-on experience shipping LLM-powered products such as assistants, agents, or copilots to real users.
Demonstrated zero-to-one product leadership, with at least one product taken from an ambiguous concept through launch, measurement, and iteration, ideally within a larger organization.
Strong working knowledge of modern AI technologies, including prompting, evaluation frameworks, agentic patterns, memory, and tool use.
Ability to engage confidently in technical discussions with ML and AI engineering teams and translate technical capabilities into customer-focused product experiences.
Strong understanding of the economics of AI in production, including cost per user and the tradeoffs between models, context, caching, performance, and product requirements.
Proven commercial and category-building instincts, with experience launching products or experiences that required establishing new market positioning and demonstrating customer value.
A clearly articulated perspective on AI autonomy, including when AI should guide, ask, or act and how users can maintain control.
Founder-style mindset with a bias toward experimentation, rapid prototyping, learning through shipping, and navigating ambiguity.
Executive-level communication skills, with the ability to turn complex and emerging concepts into clear narratives that align senior stakeholders and cross-functional teams.
Strong analytical and measurement discipline, with the ability to establish meaningful success metrics for products without established benchmarks.
Ability to let evidence and user data inform or challenge initial product assumptions.