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 |
|---|---|---|
| Senior Customer Solutions Manager, Aerospace and Satellite This role is for a Senior Customer Solutions Manager at Amazon Web Services (AWS) within the Aerospace & Satellite team. The primary focus is to act as a trusted advisor to senior stakeholders in aerospace and satellite organizations, guiding them on cloud technology and AI adoption to accelerate their missions. The role involves leading complex customer engagements, driving strategic execution of cloud adoption roadmaps, and accelerating value through modernization, generative AI, and agentic AI. It also includes enabling customers for responsible AI adoption and navigating ambiguity in dynamic situations. The role emphasizes understanding customer goals and driving end-to-end execution across AWS teams to deliver business outcomes. | Agent | 7 |
| Sr Manager, International Shopping AI Product, Alexa for Shopping Senior Manager, Product Management, AI Shopping, International to lead a team of Product Managers and Editors who help train AI models to deliver helpful, delightful conversational experiences for customers. This role advocates for and supports product parity efforts across international marketplaces by evaluating features pre-release and producing locally relevant insights to guide refinements. They guide efforts to automate evaluations, tune prompts, and localize experiences, enabling our AI Shopping initiatives to scale internationally. The team delivers delightful, locally relevant conversational experiences through LLM data curation and editing, evaluation, and prompt engineering. |
| Post-trainData |
| 7 |
| Principal GenAI GTM Specialist, WWSO This Principal GenAI GTM Specialist role focuses on driving enterprise adoption of Generative AI across EMEA, specifically leveraging Amazon Bedrock and agentic architectures. The role involves developing and executing go-to-market strategies, translating technical capabilities into business outcomes, and acting as a thought leader and trusted advisor to senior customer stakeholders. It requires a blend of deep technical proficiency in GenAI and commercial acumen to land AI transformation programs. | Agent | 7 |
| Sr AI Editorial Lead (Portuguese), AI Shopping, International This role focuses on curating and evaluating content to train and optimize AI models for conversational shopping experiences in new marketplaces and languages. It involves defining guidelines, ensuring response quality, analyzing errors, and creating frameworks for prompt tuning and management. The role also guides the development of automation and internal tools for editorial curation and evaluation, collaborating with product, science, and engineering teams. | Post-trainData | 7 |
