Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
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.
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 |
|---|---|---|
| Software Development Engineer, Neuron Foundation Tools Software Development Engineer responsible for developing and maintaining high-performance monitoring and profiling tools for AWS Neuron AI accelerators (Inferentia and Trainium). The role involves managing the full development lifecycle of the Neuron Profiler/Tools toolchain, optimizing ML Kernels and Frameworks, and collaborating with compiler and runtime teams to provide insights for customer optimization of AI workloads. | Serve | 5 |
| Principal Product Manager - Kernels, AI/ML, Annapurna Labs The Principal Product Manager will define and drive product strategy for the Neuron Kernel Interface (NKI), a compiler library for custom kernel development and optimization on AWS Neuron ML chips. This role involves working backward from customer needs, defining kernel library features, and improving the developer experience for custom kernel development, requiring a deep understanding of compiler systems, kernel optimization, and hardware acceleration. |
| Serve |
| 5 |
| Sr. Worldwide Specialist Solutions Architect - HPC/ML, Computer Aided Engineering (CAE), Weather & GPU Computing Senior Solutions Architect specializing in High Performance Computing (HPC) and Machine Learning (ML) on AWS. The role involves designing cloud-based solutions for customers with complex HPC/ML workloads, including CAE, Weather, and GPU computing. Responsibilities include collaborating with sales teams, providing thought leadership, and assisting customers in architecting and migrating their applications to AWS. | Serve | 5 |
| Software Development Engineer, Neuron Foundation Tools Software Development Engineer for AWS Neuron Foundation Tools Team, responsible for developing and maintaining high-performance monitoring and profiling tools for AI accelerators (Inferentia, Trainium). Focus on optimizing AI workloads by providing insights into performance bottlenecks and system behavior, improving ML Kernels and Frameworks. Manages the full development life cycle of the Neuron Profiler/Tools toolchain, collaborating with cross-functional teams on C++ compiler and runtime, and supporting frameworks like PyTorch, JAX, and XLA. | Serve | 5 |
| ML Compiler Engineer II - Neuron Kernel Interface , Annapurna Labs ML Compiler Engineer II on the Neuron Compiler Automated Reasoning Group, developing and maintaining tooling (fuzzers, specification synthesis) for an LLVM-based compiler that optimizes ML models for custom ML accelerators (Inferentia/Trainium). Focus on accuracy and reliability of the compiler stack. | Serve | 5 |