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 |
|---|---|---|
| Applied Scientist, Last Mile Delivery Automation This role focuses on developing AI and ML solutions for last mile delivery automation, combining expertise in machine learning, computer vision, and robotics to solve complex challenges in perception, navigation, and path planning. The scientist will research, design, and implement algorithms, transforming research concepts into production-ready solutions for autonomous systems. | ShipAgent | 8 |
| Senior AI Solution Architect Senior AI Solution Architect for AWS, focusing on helping customers adopt and scale GenAI/ML and Agentic technologies in production. This role involves building technical relationships, designing scalable architectures, providing expert guidance on AWS AI services, and contributing to the development of best practices and technical content. |
| AgentServe |
| 8 |
| Machine Learning Scientist - GenAI, KIT Machine Learning Scientist role focused on Generative AI within AWS, aiming to identify customer needs and improve cloud adoption. The role involves building Agentic AI systems, fine-tuning LLMs, applying Reinforcement Learning, and generating insights from large datasets, with a focus on taking ideas from conception to production. | AgentPost-train | 8 |
| Applied Scientist II, Alexa AI Applied Scientist II at Amazon Alexa AI focused on prototyping, optimizing, and deploying ML algorithms in Generative AI. Responsibilities include research, building PoCs, collaborating with teams, technical communication, documentation, and publishing research. | Post-train | 8 |
| Data Scientist, SPX AI Lab, SPX Science Data Scientist to build and launch production-grade agentic capabilities for Amazon Seller Assistant, a multi-agent GenAI system. Responsibilities include analyzing seller pain points, designing measurement frameworks, applying NLP and statistical modeling, and collaborating with cross-functional teams to improve the seller experience at Amazon's scale. | Agent | 8 |
| Senior Software Development Engineer , Stores Foundational AI - Rufus Senior Software Development Engineer focused on building and scaling foundational LLMs for Amazon Stores. The role involves architecting and building ML infrastructure for LLM training and post-training workflows (fine-tuning, RL, continuous learning), transforming customer interactions into training signals, optimizing RL systems, and partnering with scientists to productionize frontier techniques like RLHF and agentic workflows. Emphasis on end-to-end system ownership, including design, implementation, deployment, and observability, with a focus on low-level optimization like CUDA kernels and ML platforms. | Post-trainServe | 8 |
| Sr. Applied Scientist, Amazon Robotics, Structured Field Coordinated Planning & Control Senior Applied Scientist role focused on AI-driven structured field robotics, including path planning, fleet coordination, and control systems. The role involves leading research, translating breakthroughs into production solutions at scale, and owning end-to-end delivery of algorithmic solutions. It requires a PhD or Master's with significant experience in robotics, ML, and algorithm development, with a focus on publishing research and mentoring junior scientists. The team operates at the intersection of planning, algorithmic, and ML research with production systems. | AgentServe | 8 |
| Senior AI Solution Architect This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments. The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation. You’ll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging GenAI/ML and Agentic projects. | AgentServe | 8 |
| Senior Software Engineer, Speech MLOps Senior Software Engineer focused on MLOps for speech synthesis and GenAI experiences, involving building and maintaining ML infrastructure for the entire lifecycle on AWS. | ServePost-train | 8 |
| Applied Scientist II, Foundation Model, Industrial Robotics Group The Applied Scientist II role focuses on developing and improving machine learning systems for industrial robotics, specifically leveraging and adapting foundation models for tasks like perception, reasoning, and action. This involves fine-tuning, optimization, experimentation, and building evaluation frameworks, with a contribution to data and training workflows. The goal is to enable generalization, multi-modal learning, and skill acquisition in robots operating at Amazon's scale. | AgentData | 8 |
| Senior Applied Scientist, Alexa Ads Senior Applied Scientist role at Amazon focusing on Generative AI for Alexa Conversational Ads and Personalization. Responsibilities include defining scientific vision, leading ML projects, architecting large-scale ML systems, mentoring junior scientists, and collaborating with product/engineering. Requires experience in building ML models for business applications, ML/LLM fundamentals, and large-scale systems. Preferred experience in ad tech and building ML models for recommendations, ads ranking, personalization, or search. | ShipAgent | 8 |
| Applied Scientist, End User Messaging, AWS Applied AI Solutions Core Services This role focuses on developing advanced machine learning approaches and agentic systems for trust and safety in AWS cloud communication services. The primary goal is to create behavioral detection models and intelligent resource allocation algorithms that adapt to evolving threats and optimize service delivery. The role involves researching novel AI agent applications in security, integrating science components into production, and conducting rigorous experimentation. | Agent | 8 |
| Applied Scientist, Geospatial & Safety Science Applied Scientist role focused on leveraging computer vision, generative AI, and deep learning to enhance vehicle navigation and ensure safe, efficient deliveries by analyzing multimodal data. The role involves building large-scale ML systems, translating business requirements into prototypes, and optimizing models for production and edge devices. | ShipPost-train | 8 |
| AI Principal Product Manager-Technical, Alexa Responsible AI The AI Principal PMT for Alexa Responsible AI will define the standard for how Alexa earns and keeps customer trust. This role owns the product discipline of Responsible AI, defining customer experiences for safety guardrails, trust signals, and evaluation frameworks. The PMT will set product vision and strategy, lead cross-functional alignment across Applied Science, Engineering, Legal, Policy, and UX, and ensure the full responsible product experience including safety, privacy, and security. The role requires technical depth in LLMs and AI safety, understanding how models fail and writing requirements for safety model development and evaluation system design. The PMT will also mentor other PMs and influence Responsible AI scaling across Alexa. | Eval GatePost-train | 8 |
| Applied Scientist, Sales AI This role focuses on building AI/ML solutions for the Ad Sales business, specifically creating customer-facing recommendations and enhancing end-to-end workflows with Generative AI. The scientist will leverage quantitative modeling techniques like Sequential Recommender Systems, Deep Learning, and Reinforcement Learning, and use NLP and Generative AI for explainability. The role involves research, model development, A/B testing, and collaboration with engineering and product teams to deliver production-ready solutions. | AgentPost-train | 8 |
| Senior Applied Scientist, Special Projects Senior Applied Scientist role focused on building state-of-the-art ML models for healthcare challenges within Amazon's Special Projects team. The role emphasizes practical implementation, driving ML advancements, and delivering products to market in an entrepreneurial, startup-like environment. Requires a strong background in AI/ML, leadership skills, and the ability to translate research into actionable plans and practical solutions. | Ship | 8 |
| Applied Scientist , Amazon Applied Scientist role at Amazon focusing on improving shopping experiences using LLMs. The role involves post-training of LLMs, including instruction tuning, reward modeling, and reinforcement learning. Responsibilities include designing and running large-scale experiments, analyzing model behavior, and developing new training recipes to enhance capabilities like reasoning and user experience. Requires a PhD or Master's with significant experience, practical LLM experience, and a strong publication record. | Post-trainPretrain | 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 |
| 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 |
| Applied Scientist, Console Science The Applied Scientist will work on building industry-leading Conversational AI Systems, focusing on Natural Language Understanding, Dialog Systems, Generative AI with LLMs, and Applied Machine Learning. The role involves developing novel algorithms and modeling techniques to advance human language technology, impacting millions of customers through products and services. The scientist will gain hands-on experience with Amazon's text, structured data, and large-scale computing resources. | Post-trainAgent | 8 |
| Sr Manager Research Science, Last Mile Science and Analytics This role focuses on applying AI and machine learning to optimize Amazon's last-mile delivery network. Responsibilities include developing sophisticated ML models for logistics, forecasting, and resource allocation, architecting AI-powered systems, implementing deep learning for image recognition, and developing reinforcement learning for adaptive scheduling. The role also involves designing AI agents for autonomous decision-making and creating models for customer behavior analysis. A strong emphasis is placed on research, publishing findings, and leveraging big data and cloud platforms. | AgentData | 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 |
| Applied Scientist II, Foundation Model, Industrial Robotics Group Applied Scientist II role focused on developing foundation models for industrial robotics, integrating multi-modal learning, skill acquisition, perception, and environmental understanding. The role involves leveraging, adapting, and optimizing state-of-the-art models, conducting rigorous experimentation, building evaluation benchmarks, and contributing to data and training workflows. It requires strong programming skills in Python and experience in deep learning areas like computer vision, multimodal models, or RL for robotics. | Post-trainAgent | 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 |
| 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 |
| Member of Technical Staff, PMT Research, AGI Autonomy Product Manager - Technical role for an AGI Autonomy Lab focused on developing foundational capabilities for AI agents. The role involves defining and prioritizing tooling roadmaps for data collection, model evaluation, and release processes, bridging research and engineering by translating technical needs into product requirements. Key focus areas include combining LLMs with RL for reasoning, planning, learned world models, and generalizing agents to physical environments. | AgentEval Gate | 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 |
| 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 |
| Applied Scientist, Last Mile Delivery Automation Applied Scientist role focused on developing AI/ML solutions for Last Mile Delivery Automation, combining expertise in machine learning, computer vision, and robotics for perception, navigation, and path planning. The role involves transforming research into production-ready solutions and collaborating with engineering teams. | AgentServe | 8 |
| Applied Scientist II, Business Data Technologies This role focuses on designing and deploying GenAI, NLP, and Computer Vision solutions for Amazon's retail business services, aiming to enhance customer experience and operational efficiency. The scientist will develop novel ML techniques for task automation, text and image processing, and anomaly detection, with a strong emphasis on LLM Agents and multi-modal understanding. | AgentPost-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 |
| 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 |
| Applied Scientist II, Amazon Smart Vehicles The Amazon Smart Vehicles (ASV) science team is seeking an Applied Scientist with expertise in advanced LLM technologies to create personalized services for drivers and passengers, enhancing their experience on the road. The role involves innovating in AI research, developing novel algorithms, and applying theoretical models in an applied environment, with direct application to Amazon products. The scientist will leverage Amazon's data and computing resources to advance generative AI and work closely with other teams to drive impact. | Agent | 8 |
| Amazon Industrial Robotics - Applied Scientist II Intern / Co-op - 2026, Amazon Industrial Robotics This role focuses on developing next-generation advanced robotics systems by combining AI, control systems, and mechanical design for automation at Amazon's scale. The intern will contribute to research bridging theoretical advancements and practical implementation in robotics, focusing on areas like dexterous manipulation, locomotion, and human-robot interaction, leveraging deep learning and LLMs. | Ship | 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 |
| 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 |
| 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 |
