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

Amazon Amazon · Big Tech · Hawthorne, CA · Data Science

This role is for an AI Platform Builder, a Data Engineer focused on developing Platforms and Agentic AI solutions. The role involves designing, implementing, and maintaining data pipelines and platforms that power AI/ML initiatives, using AI for code generation, optimization, and building AI-native self-service data platforms. It emphasizes prompt-driven development and creating self-improving systems.

What you'd actually do

  1. 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.
  2. 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.
  3. Lead AI-assisted stakeholder engagement sessions across verticals like Subscriptions, Security, Sales, and Marketing
  4. Design and build curated datasets leveraging AI code generation and Agentic AI tools
  5. Build and maintain data pipelines using AI-assisted development with AWS services and internal Amazon tools

Skills

Required

  • 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 have

  • Experience mentoring team members on best practices
  • 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

What the JD emphasized

  • AI-native self-service data platforms
  • agentic frameworks
  • AI-assisted development
  • prompt engineering
  • Agentic AI tools
  • AI coding assistants

Other signals

  • AI-first development methodology
  • AI-powered platforms
  • intelligent agents
  • AI-assisted development