Principal Product Manager

Role overview

Own the product direction and quality of an AI agent that helps customers handle household technology needs, such as device problems, activations, claims, and upgrades. This hands-on product-building role takes ambiguous customer problems from discovery through prototypes, evaluation, launch, and iteration, working closely with engineering, design, data science, and domain teams. The initial focus is establishing how agent quality is measured and improving the agent’s reasoning and coordination across high-value customer journeys.

Responsibilities

- Own the agent’s reasoning runtime and product lifecycle, from opportunity discovery and product thesis through launch, adoption, and iteration. - Define how the agent coordinates with skills, tools, other agents, and the broader technology stack. - Build offline and online evaluation systems that measure whether the agent is useful, trustworthy, and ready for customers; use results to guide shipping decisions. - Partner with engineering on reliable architecture, observability and tracing, human oversight, guardrails, and production readiness. - Build evidence for product decisions through working demos, customer research, evaluation results, and clear decision documents. - Align product, design, engineering, data science, field, legal, security, and executive stakeholders around decisions needed to deliver dependable agent capabilities.

Requirements

- At least 8 years of product management experience. - Track record taking a product from concept to first customers, revenue, or measurable business impact. - Ability to combine customer evidence, product metrics, and sound judgment to make high-stakes decisions with incomplete information. - Hands-on use of modern AI tools to prototype, analyze, write, test, research, or automate product work.

Nice to have

- Experience building or shipping AI agents, LLM features, agent orchestration, workflow automation, or decision-support systems. - Familiarity with agent evaluation and reliability, including failure analysis, human-in-the-loop design, permissions, auditability, and observability tools. - Experience with design partner, early adopter, or lighthouse customer programs.