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# Rahul Shivroop

**Headline:** Professional profile
**Location:** Seattle, WA, USA

## About

Rahul Shivroop is a product manager whose most recent role was Senior Product Manager Intern at Amazon. Rahul builds AI-enabled customer-support and returns-platform products, with particular strength in turning messy data into logical customer-return insights and driving data-backed changes across teams. At Amazon, Rahul designed an evaluation harness for a returns platform and supported a taxonomy redesign projected to deliver $450 million in annual savings through improved categorization. Earlier, Rahul built AI products using GPT-3.5 for multilingual customer-support automation. At Joro, Rahul built a customer-success chatbot that reduced ticket volume by 40% and cut resolution time from eight hours to two hours. Rahul’s work combines end-to-end product ownership, cross-functional coordination, and thoughtful safeguards for human involvement in automation.

## Highlights

- Built a customer-success chatbot at Joro that reduced ticket volume by 40%.
- Reduced customer-support resolution time at Joro from eight hours to two hours through a chatbot.
- Designed an evaluation harness for a returns platform at Amazon.
- Supported a returns taxonomy redesign at Amazon projected to deliver $450 million in annual savings through improved categorization.
- Most recently served as a Senior Product Manager Intern at Amazon.
- Built early AI products using GPT-3.5 for multilingual customer-support automation.
- Turns messy data into logical customer-return insights.
- Drives data-backed change through cross-team coordination.
- Brings end-to-end ownership and thoughtful human-automation safeguards to product work.

## FAQ

### What does Rahul do?

Rahul Shivroop most recently served as a Senior Product Manager Intern at Amazon. Rahul has also built AI-enabled customer-support products at Joro and earlier used GPT-3.5 for multilingual support automation.

### What are Rahul's core strengths?

Rahul is strongest at converting messy data into logical customer-return insights, coordinating teams around data-backed changes, and owning AI automation products end to end with thoughtful human safeguards.

### What did Rahul accomplish at Amazon?

At Amazon, Rahul designed an evaluation harness for a returns platform. The work supported improved categorization through a taxonomy redesign projected to generate $450 million in annual savings.

### What did Rahul accomplish at Joro?

Rahul built a customer-success chatbot at Joro that reduced ticket volume by 40% and decreased resolution time from eight hours to two hours.

### What AI product experience does Rahul have?

Rahul has early experience building AI products with GPT-3.5 for multilingual customer-support automation.

### How does Rahul approach automation?

Rahul emphasizes end-to-end ownership and thoughtful safeguards for human involvement in automation while using AI to support customer-service workflows.

## Links

- LinkedIn: https://www.linkedin.com/in/ACoAABpqqFUBHBLIueYo5at1EE2B1vTWvaFRprg

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