Product Manager - Technical, AI Voice, Ring & Blink Customer Service Technology
Amazon - Hawthorne, California, USA
Posted May 20, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
- $151K-$205K not verified - source not recorded; timestamp not recorded
- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Product Manager - Technical, AI Voice, Ring & Blink Customer Service Technology Hawthorne, California, USA We are seeking a Product Manager - Technical to own Ring and Blink's AI Voice products end-to-end, from strategic vision through production operations. This role leads the product direction for Ring's and Blink's AI voice agents, which collectively handle hundreds of thousands of customer calls per month across US and international markets. The CS Technology Enablement team builds the AI and platform products that power Ring and Blink's customer service organization. We operate at the intersection of conversational AI, contact center technology, and customer experience, shipping products built on Amazon Connect, Salesforce Service Cloud Voice, Amazon Bedrock, and purpose-built voice AI infrastructure. We move fast, measure everything, and iterate weekly based on real production data. Our work succeeds only when customers get their problems solved. Key job responsibilities - Own the Complete Product Lifecycle: Define strategic vision and multi-quarter roadmaps for voice AI products. Drive cross-functional execution across engineering, operations, data science, and vendor partners. Maintain accountability for containment, resolution, CSAT, and cost-per-contact outcomes. - Drive Weekly Product Improvement Cycles: Review production performance data at the intent, market, and interval level. Identify failure modes, conduct root cause analysis, and translate findings into prioritized product improvements. - Navigate Technical Complexity: Make informed tradeoffs across LLM architectures (Bedrock, third-party), prompt strategies, intent classification approaches, and dialog management designs. Distinguish between one-way and two-way door decisions in a rapidly evolving AI landscape. - Manage Vendor and Platform Partnerships:
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