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 |
|---|---|---|
| Applied Scientist, EU INTech Consumer Selection Discovery, NintAI Applied Scientist role focused on building and deploying AI/ML models for Amazon's global search and discovery experiences, with an emphasis on computer vision, generative AI, recommendation systems, and ranking. The role involves end-to-end ownership from problem analysis to production deployment, aiming to improve customer navigation and product discovery. | Ship | 9 |
| Applied Scientist, EU INTech Consumer Selection Discovery, NintAI Applied Scientist role focused on building and deploying AI/ML models for Amazon's global search and discovery experiences, aiming to improve customer navigation and product discovery. The role involves end-to-end ownership from problem analysis and science plan design to production deployment, with a focus on ranking, computer vision, and generative AI. | Ship |
| 8 |
| Applied Scientist, EU INTech Consumer Selection Discovery, EU InTech Consumer Selection Discovery Amazon is seeking Applied Scientists to build software and machine learning models for customer discovery experiences, focusing on ranking, recommendations, and computer vision. The role involves developing and deploying state-of-the-art models, including text-to-image and image-to-text, to enhance customer engagement with the Amazon catalog. | Ship | 8 |
| Machine Learning Scientist / Applied Scientist, EU Prime and Marketing Analytics & Science (PRIMAS) This role focuses on designing and executing experiments to measure the effectiveness of marketing campaigns at Amazon scale. The scientist will build measurement frameworks, apply causal inference methods, and establish experimental standards for lifecycle marketing, ultimately guiding marketing strategy and investment decisions. The role is within the consumer domain and involves scaling existing AI/ML applications. | Ship | 7 |
| Machine Learning Engineer, Amazon Tablets ML Engineer role focused on building and deploying AI/ML products for Amazon Tablets, specifically enhancing customer engagement through personalized recommendations and content ranking. The role involves end-to-end ML pipeline development, MLOps, and leveraging deep learning, LLMs, and generative AI for on-device experiences. It emphasizes shipping customer-facing ML solutions at Amazon scale. | ShipServe | 7 |
| Senior Software Development Engineer, Discovery Tech Senior Software Engineer to lead the design and evolution of AI-driven systems for generating, selecting, and optimizing marketing and merchandising assets at scale across Amazon worldwide. The role involves building systems that automatically produce and adapt images, text, and multimodal content, balancing creative flexibility, brand constraints, and performance. It requires end-to-end ownership across model integration, distributed services, and measurement frameworks, with a focus on architectural leadership and mentoring. | ShipAgent | 7 |