Staff Product Manager, AI Voice

Responsibilities

• Contribute to the strategy and roadmap for AI Voice — setting the vision for how Canary's conversational AI handles guest interactions at scale, and making the calls on what ships and when.
• Proactively surface gaps in AI accuracy, resolution rates, and system performance before customers escalate them, and turn those findings into a prioritized plan.
• Stay directly connected to enterprise hotel clients and internal stakeholders to translate real operational pain points — staffing constraints, call volume spikes, multilingual guests — into product improvements.
• Partner with Engineering, AI/ML, and Infrastructure to champion a platform-first approach: high availability, low latency, and the ability to scale across thousands of properties.
• Define and track the KPIs that actually matter — resolution rate, accuracy, latency, containment — and use that data to drive decisions, not just report them.
• Bring engineering, sales, and customer success into alignment around shared goals, especially as new AI capabilities move from development into enterprise rollout.

Qualifications

• 7+ years in product management, with a track record of shipping and scaling AI or conversational AI products in an enterprise SaaS environment.
• Real technical depth in conversational AI — LLMs, NLP, dialog management, and the infrastructure underneath — enough to lead conversations with engineers and make smart build vs. buy calls.
• A track record of driving alignment across engineering, data science, and commercial teams without direct authority.
• The ability to connect AI performance to business outcomes.
• Experience staying close to enterprise customers and clear examples of how that changed what you built.

Compensation

Target cash compensation ranges from $250,000 - $300,000, including a fixed annual salary and a performance-based bonus paid quarterly. This role also includes a stock option grant, subject to board approval. Actual compensation will be commensurate with the candidate's skill level, experience, and specific work location.