AI Builder, Ring

Amazon Ring team is leading the next phase of AI adoption and is seeking a hands-on Engineer-AI Builder. Engineers are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs.

As part of the Ring organization, AI engineers work with customers who have complex challenges that require expert-level knowledge to solve. AI engineers craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve building AI based solutions for improving operational excellence.

SPE play a critical role in capturing customer feedback, advocating for roadmap enhancements and anticipating customer requirements as they work backwards from their needs. As domain experts, AI engineer also participate in field engagement and enablement, producing content such as whitepapers, blogs, and workshops for customers, partners, and the AWS Technical Field.

This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments.

Key job responsibilities

• Build technical relationships with internal and external customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the AI builder solutions at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organization.
• You"ll automate program management, product management operations through applying AI Agents.
• You"ll be the champion of leveraging GenAI, RAG and Agentic technologies as applicable for the operational excellence
• Internally, you will be the voice of the customer, sharing their needs with regard to their usage of Gen AI services.
• In this role, your creativity will link technology to tangible solutions, with the opportunity to define cloud-native GenAI/ML and Agentic architectural patterns for a variety of use cases.
• You will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about running GenAI/ML and Agentic workloads (e.g. through workshops, user groups, meetups, online videos or conferences).
• Technical Leadership & Mentorship: Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization.