Sr. AI Platform Data Engineer, Ring Decision Science

Amazon•Hawthorne, CA

About The Position

We seek an AI Platform Builder—a Data Engineer focused on developing Platforms and Agentic AI solution—who embraces prompt-driven development with strong technical, analytical, communication, and stakeholder management skills. This role sits at the intersection of data engineering, business intelligence, and platform engineering—requiring partnership with software development engineers, scientists, data analysts, and business stakeholders across various verticals. You will design, evangelize, and implement platform features and curated datasets that power Artificial Intelligence/Machine Learning (AI/ML) initiatives and self-service analytics, helping us provide a great neighbor experience at greater velocity. This role requires a first-principles approach to leveraging AI at every layer of the data stack—from using AI agents to write and optimize code, to building AI-powered platforms that serve AI models, to deploying intelligent agents that make data accessible. You will use AI to build AI infrastructure, automate the automation, and create self-improving systems that continuously enhance data quality, discoverability, and usability.

Requirements

5+ years of data engineering experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
Experience developing, deploying and managing AI products at scale
Experience with data modeling, warehousing and building Extract, Transform, and Load (ETL) pipelines for both analytics and ML use cases
Experience building datasets or features for machine learning models or self-service analytics
Extensive hands-on experience with Generative AI (GenAI) enhanced development pipelines, AI coding assistants, and prompt engineering
Demonstrated ability to build tools, frameworks, or platforms that enable others

Nice To Haves

Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Experience building multi-agent systems, LangChain/LangGraph applications, or custom AI agent frameworks
Experience with prompt engineering, Retrieval-Augmented Generation (RAG) systems, and Large Language Model (LLM) fine-tuning
Experience with BI tools (QuickSight, Tableau, Looker) and designing datasets for analytical consumption
Experience building or contributing to AI-native self-service data platforms, feature stores, or intelligent data cataloging systems

Responsibilities

Build and maintain efficient, scalable, and privacy/security-compliant data pipelines, curated datasets for AI/ML consumption, and AI-native self-service data platforms using an AI-first development methodology.
As a trusted technical partner to business stakeholders and data science teams, you'll deliver well-modeled, easily discoverable data optimized for specific use cases while leveraging AI-powered solutions and agentic frameworks to build continuously improving systems.
Lead AI-assisted stakeholder engagement sessions across verticals like Subscriptions, Security, Sales, and Marketing
Design and build curated datasets leveraging AI code generation and Agentic AI tools
Build and maintain data pipelines using AI-assisted development with AWS services and internal Amazon tools
Implement AI-powered self-service platforms with natural language interfaces
Create intelligent governance systems for data classification, PII detection, and lineage tracking
Facilitate AI-augmented workshops for stakeholders to explore data capabilities collaboratively

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