AI Platform Data Engineer II, Ring Decision Science

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DESCRIPTION:

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.

Key job responsibilities
You will 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.

A day in the life
This Role will:

* 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

About the team
The Analytics & Science team for Decision Sciences is at the forefront of Ring's transformation into an AI-powered organization. We address cross-organizational data models, develop governance frameworks, provide direct Business Intelligence (BI) support across multiple teams, and build customer-facing and internal AI tools that fundamentally improve how effectively and quickly the organization makes decisions.

BASIC QUALIFICATIONS:

- 3+ years of data engineering experience

- Experience with data modeling, warehousing and building ETL pipelines
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Knowledge of distributed systems as it pertains to data storage and computing
- Extensive hands-on experience with Gen AI enhanced development pipelines, AI coding assistants (Git Hub Copilot, Amazon Q, Cursor, etc.), and prompt engineering
- Demonstrated track record of building AI agents, agentic workflows, or AI-powered automation tools

PREFERRED QUALIFICATIONS:

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions

- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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