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
- 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
This Role will:
- 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: - 5+ years of data engineering experience
- Experience with data modeling, warehousing and building Extract, Transform,
and Load (ETL) pipelines for both analytics and ML use cases
- Experience with Structured Query Language (SQL) and at least one programming
language (Python, Java, Scala, or NodeJS)
- 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 track record of building AI agents, agentic workflows, or
AI-powered automation tools
- Demonstrated ability to build tools, frameworks, or platforms that enable
others Preferred Qualifications: - Experience with AWS technologies like
Bedrock, SageMaker, Redshift, Simple Storage Service (S3), AWS Glue, EMR,
Athena, Kinesis, FireHose, Lambda, Step Functions, SageMaker Feature Store, and
Identity and Access Management (IAM) roles and permissions
- 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 in at least one modern scripting or programming language with
production-quality code standards
- Experience with non-relational databases / data stores
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis
of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our
customers. If you have a disability and need a workplace accommodation or
adjustment during the application and hiring process, including support for the
interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations
[https://amazon.jobs/content/en/how-we-hire/accommodations] for more
information. If the country/region you’re applying in isn’t listed, please
contact your Recruiting Partner.
