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, Ring Neighbors Software Development Engineer role at Amazon Ring Neighbors, focusing on building and operating large-scale cloud systems for a hyperlocal social networking app. The role involves shaping the definition, vision, design, roadmap, and development of core services, with a mention of a machine learning (ML) component ripe for future investment. The team uses Go, Python, AWS services, and works on backend services and web tools for internal customers. The primary focus is on software development, design, architecture, and cloud computing, with a future opportunity to invest in ML. | — | 0 |
| Associate Systems Engineer This role is for an Associate Systems Engineer on the AWS Region Services team in Melbourne, Australia. The primary focus is on operating and improving large software systems, troubleshooting issues, implementing Operational Excellence best practices, and automating manual processes within secure, scalable cloud environments. The role requires experience with Linux, troubleshooting scalable systems, and scripting for automation. While AI and ML are mentioned in the context of the team's work, the core responsibilities of this specific role are centered around systems engineering, operations, and support within a regulated environment. |
| — |
| 0 |
| Systems Engineer, Region Services Systems Engineer role focused on operating and maintaining secure, scalable cloud environments within AWS Region Services in Australia. Responsibilities include defining hardware requirements, developing management tools, adapting operations systems, executing acceptance tests, monitoring fleet health, and participating in on-call rotations. Requires Australian citizenship and security clearance. | — | 0 |
| SDE III, Prime Video Commerce Tech Software Development Engineer III role at Amazon Prime Video, focusing on the commerce tech platform that powers the global offer ecosystem. The role involves designing, developing, and deploying end-to-end solutions for distributed systems, security, concurrency, scalability, availability, durability, and performance engineering. The team manages the entire offer lifecycle, including TVOD rentals, purchases, channel subscriptions, and account sharing enforcement, aiming to deliver personalized and contextually relevant offers. The platform processes millions of daily transactions and supports numerous client services. While AI is mentioned for personalization and ranking, the core of the role is in building and scaling the commerce platform. | — | 0 |
| CXQO Associate, CXQO This role supports the backend non-technical operation of Amazon Go Stores by performing data collection tasks, adhering to SOPs, and participating in process improvement. It is not directly involved in AI/ML model development or deployment. | — | 0 |
| MLA IP Design Verification Engineer, Annapurna Labs The role is for a Design Verification Engineer focused on machine learning hardware in AWS data centers. Responsibilities include verifying hardware and software solutions, developing verification plans, and measuring progress. The role requires a Bachelor's degree and experience in design verification using System Verilog and UVM. | — | 0 |
| Software Development Engineer II, Amazon Software Development Engineer II at Amazon, focusing on designing and developing scalable financial systems and solutions for global financial transactions using AWS cloud technologies. The role emphasizes architectural design, software development, testing, deployment, and advocating for engineering best practices. While AI/ML experience is a plus, it is not the core focus of the role. | — | 0 |
| Senior Solutions Architect, AWS Private Equity This role focuses on helping Private Equity firms and their portfolio companies leverage cloud technologies, specifically AWS, to improve operations and build new solutions. The Solutions Architect will act as a trusted advisor, providing technical leadership and thought leadership to C-level executives and technical leaders, bridging the gap between business needs and technology solutions. The role involves educating clients on cloud capabilities, designing reference architectures, and influencing AWS's roadmap. While not directly building AI models, the role is within an enterprise AI context by helping businesses adopt advanced technologies. | — | 0 |
| System Development Engineer, Automation Integration Technologies System Development Engineer focused on integrating robotics and automation within Amazon's global fulfillment network. The role involves developing core machine control logic for industrial edge devices, designing system controls architecture, and integrating control systems with various hardware and software services. It requires experience with PLC-based controls, machine control code development, and a background in industrial automation. | — | 0 |
| Sr. Formal Verification Engineer, Annapurna Labs This role is for a Sr. Formal Verification Engineer focused on hardware design and optimization for cloud server infrastructure, including machine learning inference products like AWS Inferentia. The responsibilities involve developing formal verification plans, implementing and verifying IP architectures, and using formal methods and abstraction techniques. While the role touches on ML inference hardware, the core craft is hardware design and verification, not AI/ML model development or research. | — | 0 |
| Software Development Engineer, Last Mile Planning Software Development Engineer role focused on Last Mile Planning at Amazon, developing and owning software components for efficient and reliable package delivery. The role involves working with ML and Operations Research algorithms, but the core focus is on software engineering and delivery within the existing systems. | — | 0 |
| Amazon Robotics - 2026 Supply Chain Intern/Co-op, Robotics Supply Chain This is an internship/co-op role in Amazon Robotics focused on supply chain processes, including planning, sourcing, logistics, and systems. The role involves understanding and improving existing processes, leading automation projects, developing metrics, and supporting new product introductions within the supply chain organization. While the company utilizes AI and ML in its robotics, this specific role is centered on supply chain operations and business process improvement, not direct AI/ML model development. | — | 0 |
| Sr. Hardware Engineer - ML Acceleration, Annapurna Labs This role is for a Sr. Hardware Engineer focused on the design, definition, and validation of AWS's next-generation ML Chips and Cards, including server integration and PCIe/Serdes topics. The engineer will optimize hardware for data centers and work with cross-functional teams on large-scale server deployments. | — | 0 |
| Professional Services 인턴, A2C Internship opportunity at Amazon Web Services (AWS) focusing on cloud computing solutions. The role involves gaining hands-on experience, developing business acumen, and learning about Amazon's culture. Specializations include DevOps, Cloud Infrastructure Architecture, Application Development, Data & Analytics (potentially using ML/AI), and Security Consulting. The program offers professional development and the chance to obtain AWS certifications. | — | 0 |
| Principal Engineer, EC2 Principal Engineer on the EC2 Accelerated Nitro team, focusing on developing next-generation EC2 instance families by innovating in virtualization, hardware acceleration (GPUs, FPGAs), and cloud computing infrastructure. The role involves leading the design and architecture of core EC2 capabilities, advancing virtualization security, mentoring engineers, and influencing the future of cloud computing. Requires expertise in low-level system software and hardware acceleration. | — | 0 |
| Sr. Software Development Engineer, Annapurna Labs Senior Software Development Engineer at Amazon Annapurna Labs focused on compute sanitization for ML accelerators (Neuron). The role involves leading a technical team to develop tools for identifying hardware defects before customer impact, working closely with hardware, firmware, training, inference, and runtime teams. The goal is to ensure the functional correctness of ML hardware through pre-check and functional correctness checking suites. | — | 0 |
| Senior Business Intelligence Engineer, AMXL JP Senior Business Intelligence Engineer role at Amazon's AMXL Japan, focusing on building and operating reports, dashboards, and applications to support a large e-commerce logistics business. The role involves setting strategic priorities, delivering BI solutions, ensuring engineering and operational excellence, defining metrics, and delivering BI solutions for complex problems. Requires experience in SQL, data extraction/transformation, statistical analysis, scripting (Python), and information retrieval/data science/machine learning/data mining. | — | 0 |
| Senior Technical Program Manager - Software, AWS Center for Quantum Computing Senior Technical Program Manager to support software development efforts for quantum hardware fabrication and operation. The role involves planning and executing projects to develop tools for data ingestion, testing acceleration, and streamlining operations, aiming to drive efficiency and accelerate hardware development. It requires navigating ambiguity, making data-informed decisions, and contributing to project management standards. | — | 0 |
| Systems Development Engineer This role focuses on developing and maintaining operational systems and tools for AWS Region Services, emphasizing automation, system health monitoring, diagnostics, and incident resolution within a secure cloud computing environment. While AI and ML are mentioned as technologies used by the team, the core responsibilities are centered around engineering and operational excellence of cloud infrastructure, not direct AI/ML model development or deployment. | — | 0 |
| Systems Development Engineer This role is for a Systems Development Engineer on the AWS Region Services team in Sydney, Australia. The primary focus is on supporting and refining system requirements, developing and delivering operability features like monitoring, diagnostics, and self-healing automation. The role involves managing and improving operations for scalable, high-availability cloud services, including participating in on-call rotations and incident resolution. While the team works with AI/ML, this specific role is centered on the engineering and operational aspects of secure cloud infrastructure, not direct AI/ML model development or research. It requires experience with automation, programming languages, Linux/Unix, and ideally with distributed systems, performance tuning, and infrastructure as code. | — | 0 |