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 Machine Learning Software Development Engineer, AI Ops Integration Senior Machine Learning Engineer role focused on designing and deploying production ML/LLM systems and agentic AI solutions for Amazon Operations & Supply Chain. The role involves end-to-end system design, data pipelines, model serving, orchestration of complex workflows, and ensuring safe and reliable operation of AI systems. It requires leadership in technical design, architecture, and engineering excellence across the ML lifecycle, with a focus on automating operational decisions at scale. | AgentServe | 8 |
| Software Development Engineer II — AWS DMS Schema Conversion Team, DMS Schema Conversion Software Development Engineer II role focused on building cloud-native solutions for AWS DMS Schema Conversion, with a significant emphasis on integrating Generative AI to automate database schema and object conversion tasks for customer migrations. The role involves designing, developing, and scaling microservices, tackling distributed systems problems, and contributing to AI-powered migration tooling. |
| Agent |
| 5 |
| Software Development Engineer, AWS Incident Tooling & Response Software Development Engineer role focused on building the next generation of incident management tooling for AWS, utilizing agentic AI development practices to create a unified, highly available, and performant platform for coordinating response during critical incidents. The role involves owning significant portions of the service architecture, including the data layer, authorization system, and API model, and integrating with automation systems. | Agent | 5 |