Sr. AI Platform Data Engineer, Ring Decision Science, Ring Decision Science

Amazon
USA, CA, Hawthorne2025-12-16ONSITE

About the job

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.

Responsibilities

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

Qualifications

Minimum

Experience mentoring team members on best practices

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

Preferred

Experience operating large data warehouses

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