Amazon has 1472 active AI-related job listings. The company is heavily focused on roles within the "agents" stage, which accounts for 38% of its AI hiring, followed by "application" at 26%. Engineering is the dominant function, with 1172 positions. Over the last 30 days, Amazon has added 667 new AI roles, representing a 74% increase compared to the previous 30-day period. Frequent tech tags include agent_orchestration, model_serving, and multimodal.
Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
Amazon currently has 1573 active AI-related roles in our index. The most common open titles are: ML Data Associate-II (9), 2026 Applied Scientist Intern, Amazon University Talent Acquisition (8), AI Data Associate (Dutch) , Artificial General Intelligence Data Services (8), Software Development Engineer, AWS (8), Senior Delivery Consultant - Data , Professional Services, AWSI HCLS (7). Most positions are in Engineering and Research.
Amazon's active AI hiring is concentrated in: agents (41%), application (26%), serving infrastructure (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Amazon is hiring AI talent in: United States (1023 roles), Canada (59 roles), United Kingdom (47 roles), India (23 roles).
Job postings at Amazon most frequently mention: Machine Learning, Generative AI, Large Language Models (LLMs), Software Engineering, Agentic Systems.
In the past 30 days, Amazon has posted 696 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| AI Language Engineer, Alexa for Shopping AI Language Engineer for Amazon's Conversational Shopping team, focusing on developing and implementing LLM-assisted evaluation tools and processes to improve AI-driven shopping experiences. The role involves creating automated verification scripts, annotation guidelines, and quality metrics, collaborating with cross-functional teams to ensure high-quality editorial data and product outcomes. | Eval GateData | 8 |
| Applied Scientist, Fauna This role focuses on developing evaluation frameworks and data collection protocols for robotic capabilities, bridging robotics, ML, and human-in-the-loop systems. The scientist will design evaluation methodologies, create data collection protocols, build teleoperation workflows, and analyze results to improve robot behavior and dataset generation. |
| 7 |
| Software Development Engineer Test, Alexa Global quality Software Development Engineer in Test focused on quality assurance automation and framework creation for Alexa's global, multilingual, and multimodal experiences. The role involves building agentic automation tooling for end-to-end quality evaluation, including synthetic test generation, LLM-as-a-Judge, and visual/cultural validation using ML. | Eval GateAgent | 7 |