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 11% 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 |
|---|---|---|
| Compiler Engineer II - Machine Learning, Annapurna Labs The role involves developing and scaling a deep learning compiler stack for AWS Machine Learning accelerators (Inferentia and Trainium chips). The engineer will architect and implement features for the AWS Neuron SDK, focusing on making LLM and Vision models run performantly on accelerators. This includes compiler development, optimization, and integration with ML frameworks like PyTorch, TensorFlow, and JAX. | Serve | 8 |
| Applied Scientist II, Kiro Science Applied Scientist II role focused on building AI-based services for Amazon Q Developer, aiming to redefine developer workflows. The role involves working on ambiguous problem areas, driving the delivery of end-to-end modeling solutions, and collaborating with other AWS AI services. The team builds AI products deployed in IDEs, AWS console, and web tools, providing developers with AI assistants for code generation and AWS interaction. | Ship |
| 8 |
| Principal Data Scientist, WWPS ProServe Principal Data Scientist role at Amazon ProServe, focusing on architecting and implementing enterprise-scale AI/ML and generative AI solutions for customers. Requires technical leadership, strategic advisory, and developing reusable frameworks. Involves customer-facing engagements and mentoring junior data scientists. Requires Top Secret clearance. | ShipServe | 8 |
| Neuron Collectives Software Engineer, Trainium Collectives Software Engineer role focused on enhancing collective algorithms and topologies for optimal AI training performance on Amazon's Trainium chips. This involves optimizing communication primitives to scale AI compute across data centers, working closely with hardware teams, and developing C/C++ implementations for training LLMs. | Data | 8 |
| Sr. Machine Learning Engineer, WWPS ProServe Data and Machine Learning Senior Machine Learning Engineer role focused on designing, implementing, and scaling AI/ML solutions for AWS customers. The role involves working with customers to understand their needs, select and fine-tune models, develop proof-of-concepts, and implement AI/ML solutions at scale. It also includes designing and running experiments, researching new algorithms, and optimizing for business impact. The role requires expertise in machine learning, generative AI, and best practices, with a focus on customer success and AI transformation. | Post-trainAgent | 8 |
| Sr. Data Scientist- Computer Vision, Data & Machine Learning (DML) Develop computer vision models on overhead imagery for a government customer, owning the entire ML development lifecycle from data exploration and feature engineering to model training, evaluation, and delivery. This role operates on classified networks and requires a Top Secret security clearance. | Post-trainData | 8 |
| Principal Data Scientist, WWPS ProServe Principal Data Scientist role at Amazon ProServe, focusing on architecting and implementing enterprise-scale AI/ML and generative AI solutions for AWS customers. Requires technical leadership, strategic advisory, and driving customer adoption of AWS AI/ML services. Involves leading complex initiatives, translating business challenges into technical solutions, and developing reusable frameworks. Requires a Top Secret security clearance. | ShipServe | 8 |
| Applied Scientist, Support Products & Services Applied Scientist role at Amazon Advertising focused on building LLM-based solutions for advertiser support, predicting problems, and coaching users. The role involves applying NLP techniques, developing scalable ML solutions, and working with AWS services to create customer-facing applications. | Agent | 8 |
| Support Engineer, Agentic Solutions, Relay Product and Tech This role focuses on developing and implementing Agentic AI and automation solutions for identity verification, account support, and compliance within Amazon's Relay product. The engineer will lead the end-to-end development of agentic workflows, integrate Generative AI and LLMs, and enhance existing systems to improve efficiency and reduce waste and abuse. | Agent | 8 |
| Principal Applied Scientist, AWS Marketplace & Partner Services Principal Applied Scientist at AWS Marketplace & Partner Services focused on developing and evaluating next-generation search, recommendation, and agentic systems to drive AWS revenue growth. The role involves defining technical strategy, leading innovations in information retrieval, recommendation systems, LLMs, and agentic AI, and mentoring other scientists. Key responsibilities include architecting agentic AI systems, bridging theory with practice, and contributing to the scientific community. | AgentServe | 8 |
| Senior Applied Scientist, Selling Partner Support Senior Applied Scientist role focused on building machine learning and GenAI solutions, specifically agentic frameworks, to improve customer support for Amazon's selling partners. The role involves end-to-end development, collaboration with engineers and product owners, and applying state-of-the-art ML/GenAI techniques to automate workflows and diagnose issues. | Agent | 8 |
| 2026 Annapurna Labs at AWS, Early Career (US) - Machine Learning Systems & Silicon Innovation This role focuses on building and optimizing the systems and silicon that power AI infrastructure, including custom ML accelerator chips, distributed training systems, and compiler optimizations for ML training. It's an early career role within Annapurna Labs at AWS, aiming to accelerate AI development. | Serve | 8 |
| Sr Software Development Engineer , AXU Senior Software Development Engineer focused on building and architecting sophisticated AI agent systems leveraging LLM/SLM technologies, Amazon Bedrock's agent core, and custom MCP servers. The role involves creating intelligent automation, deploying ML products, advanced prompt engineering, and integrating agent frameworks to push the boundaries of generative AI for inclusive customer experiences. | AgentServe | 8 |
| Senior Software Development Engineer, GenAI, Ads Agentic Intelligence Senior Software Engineer to lead technical vision and innovation for a new team building a horizontal agentic AI layer for Amazon Advertising. The role involves architecting and implementing robust systems using LLMs and autonomous agents to transform advertiser interactions with the platform. | Agent | 8 |
| Senior Leader, ProServe AI/GenAI/Agentic Specialists, Healthcare and Life Sciences Senior leader to build and lead a team of ProServe Cloud Architects specializing in AI, GenAI, and Agentic AI within the Healthcare and Life Sciences domain. The role involves counseling executives on AI transformation programs, developing repeatable partnership models, and designing scalable AI solutions. Requires expertise in AI/GenAI/Agentic AI within HCLS and experience in business development or professional services. | Agent | 8 |
| Machine Learning Engineer II , AGI Customization Machine Learning Engineer II on the AGI Customization team at Amazon, focusing on developing and optimizing LLM training techniques, including fine-tuning, distillation, model evaluation, and prompt optimization for multimodal LLMs and Generative AI solutions. | Post-trainData | 8 |
| Software Development Engineer (ML), AGI Customization, AGI Customization ML Engineer role focused on developing customization capabilities like fine-tuning and distillation for LLMs, advancing LLM training techniques, and optimizing multimodal LLMs and Generative AI solutions. Requires experience deploying LLMs in production and knowledge of ML frameworks. | Post-trainServe | 8 |
| Applied Scientist II, Amazon Payment Products (L5) Applied Scientist II at Amazon Payment Products focused on designing and deploying scalable ML, GenAI, and Agentic AI solutions for financial products. The role involves developing deep learning and LLM models for tasks like automation, text processing, pattern recognition, and anomaly detection, with a strong emphasis on production deployment and iterative improvement. | Agent | 8 |
| Senior Software Development Engineer, US Prime and Marketing Tech Senior Software Development Engineer role focused on leading the development and implementation of a generative marketing agentic framework (GeMA) at Amazon. The role involves designing a multi-agent architecture, establishing evaluation frameworks, and integrating AI-based solutions for personalized marketing at scale. It requires technical leadership, collaboration with cross-functional teams, and research into LLMs and multi-agent AI systems. | Agent | 8 |
| Applied Scientist, Delivery Foundation Model Applied Scientist role focused on developing and implementing novel foundation models for logistics, involving multimodal data, training at scale, and inference. The role spans from data preparation to model training, evaluation, and inference, with a focus on production environments. | PretrainServe | 8 |
| Senior Applied Scientist, Industrial Robotics Group This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will lead the design and implementation of methods for Visual SLAM, navigation, and spatial reasoning, leveraging simulation and real-world data for model development. The goal is to create a hierarchical system combining low-level control with high-level planning for dexterous manipulation and human-robot interaction. | Agent | 8 |
| Principal Software Engineer, AI Domains, Alexa AI Principal Software Engineer for Amazon's Alexa AI organization, focusing on the AI runtime backbone (Aurora). The role involves architecting and delivering large-scale, multi-modal, multi-lingual, and multi-model AI systems, including orchestration, routing, and inference optimization. Responsibilities include building evaluation infrastructure, ensuring responsible AI deployment, and defining technical strategy for AI experiences. This is a senior engineering role focused on production systems at scale. | AgentServe | 8 |
| Software Development Engineer III, Annapurna Labs Software Development Engineer III at Amazon Annapurna Labs, focused on building AI agents and tools to simplify and accelerate customer adoption of AWS Neuron, the software stack for Amazon's ML silicon (Trainium). The role involves technical leadership, research, and delivery of innovative software solutions to improve ML workload porting and optimization on AWS hardware. | Agent | 8 |
| Applied Scientist II - Gen AI & LLM, PXT Applied Scientist II role focused on designing, developing, and deploying Generative AI and LLM solutions for Amazon. The role involves working with foundation models, prompt engineering, RAG, fine-tuning, and production deployment of AI systems, with a focus on applied research and evaluation. | AgentPost-train | 8 |
| Sr Software Development Manager, Generative AI for AWS Neuron This role is for a Senior Software Development Manager leading a team to build AI agents and tools that simplify and accelerate customer adoption of AWS Neuron, a software stack for Amazon's Machine Learning silicon (Trainium). The focus is on applying Generative AI to improve the process of porting and optimizing ML workloads on Neuron, involving collaboration with scientists, engineers, and customers. | AgentServe | 8 |
| Member of Technical Staff, AGI Autonomy This role focuses on developing training environments, tasks, and integrations for scaling RL environments and core model capabilities for browser-based agents. The primary responsibility is to architect and deliver robust software solutions, including agentic harnesses, and engineer high-performance systems using TypeScript and Python. | AgentData | 8 |
| Sr. Machine Learning Engineer, AWS Applied AI Solution Senior Machine Learning Engineer at AWS Applied AI Solutions focused on building a new agentic product. The role involves transforming research into production systems, owning end-to-end deployment of Generative AI and ML methods, and establishing scalable processes for model development, validation, and serving. Requires expertise in agentic systems, production ML, and scalable deployment architectures, bridging research and customer-facing products. | AgentServe | 8 |
| Software Development Manager, Devices & Services Trust CX Innovations Software Development Manager for Amazon's Devices & Services Trust CX Innovations team, focusing on building and scaling teams that deliver privacy-first, accessible, and trustworthy AI experiences for consumer devices like Alexa and Echo. The role involves driving technical strategy for privacy-preserving AI architectures, responsible AI frameworks, and accessibility features, while balancing performance with privacy, building explainable AI systems, and creating guardrails for LLMs. Key challenges include latency vs. privacy trade-offs, AI safety at scale, ambient computing privacy, multimodal AI systems, and real-time evaluation. | ShipEval Gate | 8 |
| Applied Scientist II, Campaign and Creative This role focuses on building and deploying machine learning models for computer vision systems on robotic platforms, specifically for automotive shopping experiences. It involves end-to-end solution delivery, from design and implementation to optimization and deployment on the edge, with a strong emphasis on deep learning and computer vision techniques. | ServePost-train | 8 |
| Sr. Applied Scientist, Amazon Ads Senior Applied Scientist at Amazon Ads focusing on applying cutting-edge generative AI and LLMs to the advertising life cycle. The role involves researching, developing, and deploying ML solutions for ranking, personalization, NLP, computer vision, recommender systems, and LLMs. It requires driving end-to-end projects, building and optimizing models, running A/B experiments, and developing scalable ML processes. The role emphasizes impacting millions of customers and advertisers through innovative ML solutions at massive scale. | ShipServe | 8 |
| Senior Software Development Engineer - AI/ML, AWS Neuron Senior Software Development Engineer for AWS Neuron, focusing on accelerating deep learning and GenAI workloads on custom ML accelerators (Inferentia and Trainium). The role involves optimizing inference performance for LLMs, working across the stack from frameworks to hardware-software boundaries, and collaborating with compiler, runtime, and hardware teams. Key responsibilities include designing, developing, and optimizing ML models and frameworks, building infrastructure for model onboarding, implementing low-level optimizations, and working with customers on model enablement. | Serve | 8 |
| Software Development Engineer - AI/ML, AWS Neuron Software Development Engineer focused on optimizing and enabling deep learning and GenAI workloads, specifically LLMs, on AWS's custom ML accelerators (Neuron SDK, Inferentia, Trainium). The role involves system-level and low-level optimizations for inference performance, working across frameworks, kernels, and hardware boundaries. | Serve | 8 |
| Sr Business Research Scientist, RBS Senior technical leader to architect an intelligent decision-making platform using advanced AI/ML models for dynamic, context-aware decisions at scale. Focuses on generalized analytical patterns, multi-tenant processing, real-time context, and automated discovery within a large-scale, distributed system. The role involves building platform-level capabilities and ensuring pattern sharing while maintaining tenant isolation. | Agent | 8 |
| Applied Scientist, AWS Neuron Science Team Applied Scientist role focused on enhancing AWS software stack for Trainium and Inferentia accelerators, involving ML/RL for kernel/code generation, ML compiler techniques, system robustness, and efficient kernel development. Collaborates with customers and engineering teams to optimize ML systems and adoption. | ServePost-train | 8 |
| Sr Manager, Applied Science, Alexa Connections Senior Manager of Applied Science for Alexa Connections, leading a team to build LLM-powered communication features for millions of users. Focuses on end-to-end applied science projects, from ideation to deployment and monitoring, with an emphasis on scaling ML models and AGI/LLM systems for consumer applications. | ShipPost-train | 8 |
| Sr. AI Process Engineer, Seller Compliance Senior Process Engineer to lead AI-driven engineering initiatives in the Compliance domain, focusing on designing, building, and operating AI-powered solutions to improve Seller compliance outcomes and operational efficiency. Requires deep hands-on expertise in AI/ML development, building/deploying/scaling production AI systems, designing architectures, building ML models and data pipelines, and driving technical collaboration. Experience with Python, cloud platforms (AWS), and ML operations is essential. | Serve | 8 |
| Applied Science Manager III, RBKS AI Manager for an Applied Science team focused on innovating AI features for Ring and Blink cameras, combining computer vision and generative AI for home security. The role involves leading the team in developing and productizing advanced CV and GenAI models, driving technical strategy for privacy-preserving solutions, and ensuring delivery of high-quality science artifacts for customer-facing products. | ShipPost-train | 8 |
| Principal Applied Scientist, Sponsored Products and Brands Principal Applied Scientist role focused on developing and deploying generative AI solutions for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, building ML/LLM models for advertiser and shopper experiences, optimizing campaign performance, and leading scientific rigor. Requires strong ML, LLM, and GenAI expertise with experience in production systems and digital advertising. | ShipPost-train | 8 |
| Software Development Engineer, AI/ML, AWS Neuron, Model Inference Software Development Engineer focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium), working across the stack from frameworks like PyTorch/JAX to hardware-specific optimizations and kernel development. | Serve | 8 |
| Sr. Manager, Applied Science, Sponsored Products and Brands Senior Manager role leading a team of Applied Scientists and Engineers to develop and deploy generative AI solutions for Amazon's Sponsored Products and Brands advertising platform, focusing on multi-lingual and multi-modal applications to drive growth in non-US markets. | Ship | 8 |
| SDE- ML Engineer, Frontier AI Robotics Machine Learning Systems Engineer for Frontier AI Robotics team, focusing on building and optimizing distributed training infrastructure for large-scale deep learning and transformer models. Role involves engineering scalable, high-performance systems for AI research and applications, with a focus on robotics, multimodal perception, and manipulation strategies. Requires strong software development, ML infrastructure, and deep learning framework expertise. | Data | 8 |
| AI Platform Data Engineer, Ring Decisions Sciences Platform AI Platform Data Engineer responsible for designing, building, and maintaining data pipelines, curated datasets for AI/ML consumption, and AI-native self-service data platforms using an AI-first development methodology. The role emphasizes leveraging AI at every layer of the data stack, including using AI agents for code optimization, building AI-powered platforms for AI models, and deploying intelligent agents for data accessibility. Experience with Gen AI enhanced development pipelines, agentic workflows, and prompt engineering is mandatory. | DataAgent | 8 |
| Senior Applied Science Manager, Amazon Sponsored Products & Brands Lead a team to invent and build the SPB-Agent, a GenAI platform transforming retail-media advertising for Amazon advertisers. This agent will act as an intelligent advisor integrated into Amazon Ad Console and Seller/Vendor portals, using conversational interfaces and deep reasoning to help advertisers discover growth opportunities, optimize campaigns, and execute strategies at scale. | Agent | 8 |
| Applied Scientist III, RBKS AI The RBKS AI team at Amazon is seeking Applied Scientists to innovate AI features for Ring and Blink cameras, focusing on the intersection of computer vision, generative AI, and ambient intelligence. The role involves productizing research into advanced computer vision and multimodal GenAI models for video understanding, object detection, and real-time applications, with an emphasis on privacy-preserving, efficient fine-tuning, and on-device/in-cloud inference. The goal is to ship AI solutions that enhance home security for millions of customers. | ShipPost-train | 8 |
| Senior Applied Scientist , RBS Tech This role focuses on designing and deploying GenAI, NLP, and Computer Vision solutions to enhance customer experience and automate operations within Amazon's retail business. It involves developing novel ML models for task automation, text and image processing, and anomaly detection, with a strong emphasis on multi-modal LLM agents and retrieval systems. | AgentPost-train | 8 |
| Senior Applied Scientist, Translation Services Senior Applied Scientist role focused on applying advanced NLP and LLM techniques to improve machine translation quality and pipeline efficiency for Amazon's e-commerce platform. The role involves architecting and implementing scalable ML solutions, driving data analysis, and pioneering modeling techniques for translation quality assessment and optimization. The scientist will also serve as an expert in LLM applications for translation and mentor team members. | Post-train | 8 |
| Sr. Software Engineer- AI/ML, AWS Neuron Apps Senior Software Engineer role focused on optimizing and deploying large AI models (LLMs, vision generative AI) on AWS's custom AI accelerators (Inferentia, Trainium). The role involves architecting distributed inference solutions, optimizing performance from high-level frameworks to hardware implementations, and developing tools for LLM accuracy and efficiency. It bridges ML frameworks (PyTorch, JAX) with AI hardware, focusing on inference performance and scaling. | Serve | 8 |
| Sr. Applied Scientist, SSG Science This role focuses on optimizing and fine-tuning Generative AI models for edge platforms, working closely with custom ML hardware. The scientist will train custom models, analyze deep learning workloads, and collaborate with cross-functional teams to build ML-centric solutions for consumer devices. The role also involves publishing research and presenting at ML conferences. | Post-trainServe | 8 |
| Applied Scientist II, Strategic Account Services (SAS) Applied Scientist II role focused on developing and deploying sophisticated AI solutions for Amazon's Strategic Account Services (SAS) organization, leveraging deep learning, LLMs, and advanced ML techniques to improve seller operations and internal consultancy. The role involves end-to-end development from research to production, including architecting recommendation and optimization systems, pioneering applications of foundation models, and conducting rigorous A/B experiments. | ShipServe | 8 |
| Principal Applied Scientist, Advertiser Growth, Amazon Sponsored Products & Brands This role leads the development of generative AI applications for advertisers, focusing on agentic experiences for recommendations and guidance. It involves fine-tuning, reinforcement learning, and preference optimization, with a strong emphasis on creating customer-facing products and mentoring AI talent. | AgentPost-train | 8 |