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 |
| Partner Solutions Architect, Agentic Business Processes, AWS Partner Field EMEA Partner Solutions Architect focused on Agentic AI, working with AWS partners across EMEA to help them build and deliver AI agent solutions that automate and augment complex workflows. This involves enabling partners on Agentic Orchestration, Amazon Bedrock, and Frontier Agents, and guiding them through the Agentic Process Transformation (APT) methodology. | Agent | 7 |
| 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 |
| Process Analyst, EU Central Operations Analytics This role focuses on designing and implementing AI-powered automation solutions and machine learning models for logistics operations, aiming to enhance route planning, scheduling, and delivery execution. The analyst will leverage advanced SQL, Python/R, and AI technologies to create intelligent dashboards, predictive models, and automated reporting systems, working at the intersection of operations, analytics, and automation to drive efficiency and scale across the network. | Agent | 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 |
| Software Dev Engineer Machine Learning Software Development Engineer Machine Learning role focused on improving video and audio streaming experience for smart home devices. The role involves optimizing ML/AI frameworks for real-time inference, optimizing training pipelines, analyzing model performance, and leveraging GenAI tools for development productivity. It requires experience with video/image processing, computer vision, machine learning, and cloud computing, with a focus on scalable services and distributed systems. | Serve | 7 |
| Senior Business Intelligence Engineer, EU Stores CX Analytics & Automation Senior Business Intelligence Engineer focused on building and scaling personalized recommendations for millions of customers in EU marketplaces. The role involves developing custom models (embeddings, persona matching) using Python and Spark, building production-grade Python services, serverless infrastructure (AWS Lambda, CDK), and APIs (FastAPI) for marketing teams. It also includes owning reporting, measurement, and deep-dive analytics for personalized marketing campaigns. | AgentData | 7 |