AI Jobs & Internships at Amazon 2026
Amazon has embedded AI throughout its business — from Alexa's natural language understanding to Amazon.com's recommendation and search systems, from AWS AI services (Bedrock, SageMaker, Rekognition) to the fulfillment network's robotics and demand forecasting. The company is the world's largest cloud provider and has made its AI capabilities available to enterprises through AWS's growing portfolio of AI managed services. Amazon employs thousands of applied scientists and ML engineers who improve core business systems.
AI Roles at Amazon
Applied Scientist
ML Engineer
Research Scientist
Alexa AI Engineer
AWS AI Platform Engineer
Data Scientist
Supply Chain AI Engineer
Amazon Robotics Engineer
Work Culture at Amazon
Amazon's culture is defined by its Leadership Principles — 14 tenets including Customer Obsession, Ownership, and Bias for Action that are deeply embedded in how decisions are made and employees evaluated. The culture is demanding and performance-oriented, with high expectations for written communication (the 6-pager memo format), data-driven decision making, and long-term business thinking. The environment can feel bureaucratic in larger org units but moves very fast in product-launch contexts.
How to Get a Job at Amazon
- 1.
Master Amazon's Leadership Principles (LPs) — behavioral interview questions are structured around them and require specific STAR-format examples that demonstrate LP alignment
- 2.
Applied Scientist roles at Amazon expect ML research depth alongside software engineering — prepare both ML fundamentals and coding interview tracks
- 3.
AWS certification is valued for cloud-facing roles but less important for core ML science roles
- 4.
Amazon's bar raiser interview is a unique element — any interviewer can serve as a bar raiser who ensures candidate quality is above the team average
- 5.
Writing quality matters at Amazon — prepare to discuss how you've communicated complex technical decisions clearly to business stakeholders