Product Manager
WeaveThis Product Manager role focuses on the analytics domain, specifically building Call Intelligence products for healthcare practices. You will turn call data and AI insights into tools to improve appointment conversion and staff performance.
What you’d own
- Call Intelligence product strategy and roadmap
- AI-assisted workflows and analytics features
- Data quality, model quality, and integration trade-offs
- Product discovery with customers and internal teams
Who it’s for
A fit if you…
- ✓3–5+ years of experience in B2B SaaS, AI/ML, or communications software
- ✓Strong data fluency including SQL and product analytics
- ✓Experience managing products across distributed, cross-time-zone teams
- ✓Background in healthcare, healthtech, or contact center systems
Not for you if…
- ✗You prefer a non-technical role (requires fluency in APIs and data flows)
- ✗You prefer a localized team (requires working across India and US time zones)
- ✗You prefer high-level strategy without execution (requires driving results without formal authority)
Reading between the lines
- The mention of 'making technical trade-offs' regarding model quality suggests you will deal with the inherent unpredictability of LLM outputs.
- The requirement to 'create structure from ambiguity' implies a need for high autonomy in defining processes for the analytics domain.
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Full job description
About Weave
See all roles →Weave sells a combined phone system and patient communication suite to small healthcare practices, covering appointment reminders, missed-call texts, online scheduling, reviews, bulk email and text-to-pay in one place. Its customers are dental, optometry, veterinary, medical spa, physical therapy and primary care offices, single locations and small groups, on a subscription plus payments model. The company is based in Lehi, Utah with a second engineering hub in Noida, India, and has been listed on the NYSE as WEAV since 2021, reporting 17.4% year over year revenue growth in its first quarter of 2026. For a product manager the live problem is layering agentic AI on top of an existing phone stack, including an AI receptionist that books, answers questions and hands off to staff.
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