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 Applied Scientist Senior Applied Scientist at Amazon focused on using Generative AI, VLMs, and multimodal reasoning to understand product identity and relationships within Amazon's catalog. The role involves formulating research problems, designing and implementing models for product relationship inference and catalog understanding, pioneering explainable AI, owning ML pipelines from research to production, defining research roadmaps, and mentoring peers. It emphasizes tackling ambiguous problems at scale, reasoning across text and images, and deploying solutions that impact millions of customers. | AgentServe | 9 |
| Sr. Applied Scientist, Applied AI Solutions Senior Applied Scientist role focused on designing, developing, and evaluating long-running AI agents for AWS Applied AI Solutions. The role involves building agentic use cases, defining evaluation frameworks for complex agent outputs, and ensuring production deployment. Requires experience in building ML models for business applications and applied research. |
| Agent |
| 9 |
| Software Development Engineer, Neuron Collectives, Annapurna Labs Software Engineer role focused on optimizing collective operations for AWS Trainium, a purpose-built AI training chip. The role involves enhancing collective algorithms and topologies, optimizing compute for specific LLM training topologies, and working closely with hardware teams to maximize performance using C/C++. The goal is to scale AI compute across the data center for training frontier AI models. | Data | 9 |
| Principal Applied Scientist, Neuro-Symbolic AI Labs Research scientist role focused on building neuro-symbolic AI systems using proof assistants for complex problem-solving across various domains within Amazon. The role involves defining and implementing new applications, delivering scientific artifacts, and working in an agile environment. Requires a PhD or Master's with significant applied research experience, and experience leading scientists. | Agent | 9 |
| Applied Scientist, Alexa Connections Applied Scientist role focused on developing novel algorithms and modeling techniques for LLMs and multimodal systems within Alexa Connections. Responsibilities include analyzing customer behavior, building evaluation metrics, fine-tuning/post-training LLMs, setting up experimentation frameworks, and contributing to end-to-end delivery from research to production, with potential for publications. | Post-trainAgent | 9 |
| 2026 Fall Applied Science Internship - Gen AI & Large Language Models - United States, PhD Student Science Recruiting PhD internship focused on applied science in Gen AI and LLMs, involving fine-tuning models, developing novel algorithms for NER, recommendation systems, and question answering, and exploring generative AI applications. | Post-trainAgent | 9 |
| 2026 Fall Applied Science Internship - Natural Language Processing and Speech Technologies - United States, PhD Student Science Recruiting PhD internship focused on research in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Speech Technologies, including large language models (LLMs) and reinforcement learning with human feedback (RLHF). The role involves developing and implementing novel algorithms on production-scale data to advance the state-of-the-art. | Post-trainPretrain | 9 |
| Principal PMT-ES - AI/ML Training, Annapurna Labs Principal Technical Product Manager to define and drive product strategy for training software on AWS Trainium, including distributed training libraries, post-training workflows (RLHF, DPO, fine-tuning), reinforcement learning frameworks, and training performance optimization. The role focuses on enabling researchers and operators to train frontier models at scale. | DataPost-train | 9 |
| Postdoctoral Scientist, Amazon Robotics Research and AI Development Postdoctoral Scientist role focused on research in multi-agent path planning, dynamic optimal transport, and explainable AI for foundation models applied to a large fleet of mobile robots. The role involves developing novel techniques, publishing in top-tier venues, and potentially extending research into a second year. | AgentPost-train | 9 |
| Senior Applied Scientist, New Initiatives Senior Applied Scientist role focused on building agentic AI systems, multi-agent architectures, tool-augmented LLMs, and RAG pipelines for climate-related products. The role involves end-to-end product development from research to production, with a focus on autonomous analysis, planning, and execution of recommendations, leveraging multimodal AI and deep learning on time series data. | Agent | 9 |
| Sr. Applied Scientist, Ads AI Core Infrastructure Research and develop novel approaches for agent-data interaction using generative AI and agentic systems to provide instant, strategic advice to advertisers. Focus on agent orchestration, context optimization, code generation, and RAG-based embeddings for real-time data access with minimal latency and token consumption. Balances applied research (60%) with productionization (40%). | Agent | 9 |
| Applied Scientist Research scientist role focused on applying Generative AI, VLMs, and multimodal reasoning to product catalog understanding and agentic shopping experiences. The role involves formulating research problems, pushing boundaries of foundation models, advancing efficient model deployment, and ensuring reliability through interpretability and uncertainty calibration. It spans the full research lifecycle from problem formulation to production deployment, with a strong emphasis on publishing findings and mentoring. | AgentServe | 9 |
| Principal Applied Scientist, Conversational Assistant Modeling & Learning Principal Applied Scientist to lead science behind Alexa+, Amazon's LLM-powered conversational assistant. Owns technical direction for LLM fine-tuning, alignment, agentic reasoning, and evaluation, impacting hundreds of millions of customers. Defines research directions, designs experiments, ensures translation to production systems, mentors scientists, and represents Amazon in the research community. | Post-trainAgent | 9 |
| Senior Applied Scientist , Alexa AI Aurora Senior Applied Scientist role focused on advancing conversational AI technologies, specifically LLMs and generative AI, for Alexa. The role involves defining science roadmaps, architecting agentic systems, establishing evaluation frameworks, and driving end-to-end delivery of research initiatives from experimentation to production. Emphasis on building scalable agentic systems for conversation understanding and generation, and contributing to the team's scientific reputation through publications and patents. | AgentEval Gate | 9 |
| Principal Applied Scientist, Sponsored Products and Brands This role focuses on designing and developing generative AI solutions, specifically large language models and multimodal AI, for real-time ad allocation and ranking in a high-volume consumer advertising system. It involves research into semantic relationships, dynamic optimization, and integration into existing systems, with a strong emphasis on efficiency and strict latency requirements. | AgentServe | 9 |
| Principal, Senior Principal and Distinguished Engineer, AWS Agentic AI Seeking Principal Engineers to join AWS Agentic AI organization. This role involves designing, building, and scaling systems for AI agent platforms, services, and tools, focusing on multi-agent workflows and foundational technical infrastructure. The position requires strong technical leadership, architectural design, and the ability to drive innovation in a fast-paced environment. | Agent | 9 |
| Applied Scientist, SPX AI Lab Applied Scientist role focused on building and deploying production-grade, multi-agent generative AI systems for Amazon's Seller Assistant, impacting millions of sellers worldwide. The role involves creating next-generation tools, designing and deploying innovative models, and establishing scalable processes for model implementation and validation. | AgentShip | 9 |
| Sr. Applied Scientist, AWS Just-Walk-Out Science Team This role focuses on developing novel frameworks and techniques for multi-object tracking, re-identification, person activity understanding, and multi-modal foundation models within the context of Amazon's Just Walk Out technology. The scientist will advance the theory and practice of these areas, create efficient visual processing techniques, and reduce computational/data requirements for visual AI systems. The role requires a strong publication record in top-tier conferences and experience in computer vision, deep learning, and multi-modal foundation models. | AgentPost-train | 9 |
| Member of Technical Staff, Multimodal Reasoning - Applied Science , AGI Autonomy Applied Science role focused on developing foundational capabilities for useful AI agents, leveraging large vision language models (VLMs) with reinforcement learning (RL) and world modeling. Responsibilities include model training, dataset design, and pre- and post-training optimization in an applied research setting. | Post-trainAgent | 9 |
| Applied Scientist II, AWS Just-Walk-Out Science Team This role focuses on developing and implementing advanced visual reasoning systems and autonomous AI agents that understand complex spatial relationships, object interactions, and customer behavior patterns in real-time retail environments. It involves working at the intersection of computer vision and large language models to advance state-of-the-art visual AI. | AgentPost-train | 9 |
| Applied Scientist, LLM Code Agents, Kiro Science Research role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a goal of deploying these models into developer tools like Kiro IDE and Amazon Q Developer at Amazon scale. The role involves publishing research and transitioning breakthroughs into production systems. | Post-trainAgent | 9 |
| Senior Applied Scientist, ASCS AI Lab Team Senior Applied Scientist role focused on AI research and development, including Generative AI, Agentic AI, LLMs, and Diffusion Models for Amazon's catalog systems. The role involves designing, training, and deploying AI solutions, with a focus on scaling models and integrating them into production. | AgentPost-train | 9 |
| Sr. Principal Scientist, Amazon Health Science & Analytics Senior AI/ML researcher to define ML strategy for a healthcare foundation model and inference system, focusing on frontier models, proprietary domain models, and monetizable features under regulatory constraints. Requires expertise in training/adapting large models, distributed training, RLHF/DPO, retrieval, evaluation, and ML systems engineering, with experience in high-stakes/regulated domains. | PretrainServe | 9 |
| 2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & Robotics Internship role focused on developing novel algorithms at the intersection of LLMs and generative AI for robotics, involving research in perception, manipulation, and control. Requires strong ML/DL/robotics background and publication record. | Agent | 9 |
| 2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier AI & Robotics This internship focuses on developing novel algorithms and modeling techniques at the intersection of LLMs and generative AI for robotics, tackling research problems in robotic perception, manipulation, and control. The role involves collaboration with cross-functional teams and requires a strong background in machine learning, deep learning, and/or robotics, with a publication record at top conferences. | Agent | 9 |
| 2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & Robotics This internship focuses on developing novel algorithms at the intersection of LLMs and generative AI for robotics, involving research in robotic perception, manipulation, and control, with an emphasis on multimodal models and vision-language-action systems. | AgentPost-train | 9 |
| Applied Scientist, LLM Code Agents, Kiro Science Research role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a goal of deploying these models into developer tools like Kiro IDE and Amazon Q Developer at Amazon scale. The role involves publishing research and transitioning breakthroughs into production systems. | Post-trainAgent | 9 |
| Member of Technical Staff - Reinforcement Learning, AGI Autonomy Research role focused on developing foundational capabilities for AI agents that can act in digital and physical worlds, with a focus on multimodal LLMs, automation agent systems, and applying GenAI to real-world problems. Involves rapid invention, experimentation, and collaboration. | AgentPost-train | 9 |
| Member of Technical Staff - Reinforcement Learning (Infrastructure), AGI Autonomy Develop training infrastructure for large-scale reinforcement learning on LLMs, working across the technology stack including ML systems, orchestration, and data management. Analyze, troubleshoot, and profile ML systems, and conduct MLSys research for new techniques and tooling. | DataAgent | 9 |
| Senior Applied Scientist, Delivery Foundation Model Senior Applied Scientist role focused on developing and implementing novel deep learning foundation models, combining multiple modalities (image, video, geospatial) for logistics use cases. The role involves training models at scale, optimizing for inference, collaborating with other teams, guiding technical direction, and mentoring junior scientists. It spans the full spectrum from data preparation to model training, evaluation, and inference. | Post-trainServe | 9 |
| Sr. Principal Scientist, Secure Work Enablement Senior Principal Scientist role focused on pioneering AI technologies for secure enterprise collaboration, including novel AI architectures, human-AI interaction, AI agent orchestration, and privacy-preserving ML. The role involves translating business requirements into AI deliverables, inventing new product experiences, and bringing state-of-the-art LLM/GenAI models to production, while defining long-term science vision and collaborating with academic partners. | Agent | 9 |
| Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training Senior Software Engineer role focused on developing, enabling, and performance tuning distributed training solutions for large-scale ML models (LLMs, Stable Diffusion, ViT) on AWS Neuron accelerators using PyTorch. The role involves building distributed training support into PyTorch, the Neuron compiler, and runtime stacks, with a focus on strategies like FSDP, PP, and Context parallel. Experience with post-training strategies is a plus. | PretrainPost-train | 9 |
| Sr. Applied Science Manager, Perfect Order Experience (POE) AI Senior Applied Science Manager leading a team to develop a domain-specific LLM, including pre-training, fine-tuning, and reinforcement learning. The role also involves architecting risk detection systems using multi-modal signals and influencing ranker models for product visibility. The focus is on building and scaling AI solutions for Amazon's Perfect Order Experience. | Post-trainPretrain | 9 |
| 2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier AI & Robotics Internship role focused on developing novel algorithms and modeling techniques at the intersection of LLMs and generative AI for robotics, tackling research problems in robotic perception, manipulation, and control. Involves collaboration with cross-functional teams and leveraging expertise in deep learning, reinforcement learning, computer vision, and motion planning. | ShipAgent | 9 |
| Member of Technical Staff, Applied Science - People Leader, AGI Autonomy Lead a research team focused on advancing foundational capabilities for useful AI agents by combining LLMs with RL. The role involves managing research, aligning roadmaps, mentoring, and hiring, with a focus on evolving agents for reasoning, planning, and world modeling. Experience with training large models, scaling foundational models, and applying post-training techniques is required. | AgentPost-train | 9 |
| Delivery Consultant- AI/ML, WWPS ProServe This role focuses on designing, implementing, and scaling AI/ML solutions for AWS customers, with a strong emphasis on generative AI. The consultant will work with customers to identify use cases, select, train, and fine-tune models, and deploy these solutions. The role involves architecting complex solutions, conducting experiments, and optimizing performance, acting as a trusted advisor on AI/ML advancements. | AgentPost-train | 8 |
| Sr. Software Engineer, Alexa Connections This role focuses on designing and developing large-scale agentic AI systems for Alexa's communication features, emphasizing real-time solutions and end-to-end data excellence within a consumer product context. | Agent | 8 |
| Senior Data Scientist, Enterprise Security Products Senior Data Scientist role focused on building AI-first security products, with a strong emphasis on agentic AI, RAG, and evaluation frameworks. The role involves setting science strategy, architecting solutions, and driving adoption of AI tooling within an enterprise security context. | Agent | 8 |
| Software Development Engineer, Catalog Diagnostics (Agentic) & Analytics Software Development Engineer role focused on building agentic diagnostics and analytics services for Amazon's product catalog. The role involves using Generative AI, VLMs, and multimodal reasoning to understand product identity and relationships at a massive scale. Responsibilities include designing and implementing agentic frameworks, pioneering explainable AI, owning data pipelines, and defining product roadmaps. The team manages large data lakes and builds agentic solutions for catalog diagnostics, focusing on feedback loops, accuracy, and automated skill creation. | AgentData | 8 |
| Software Dev Engineer II, Stores Foundational AI -SFAI Software Development Engineer II role focused on building and improving generative AI for shopping using LLMs. Responsibilities include designing and implementing stable and efficient training systems for model training and reinforcement learning, developing scalable data infrastructure, and optimizing RL post-training pipelines. The role involves collaborating with scientists and engineers to accelerate innovation and translate research into production-ready systems. | Post-trainData | 8 |
| Software Dev Engineer II, Stores Foundational AI -SFAI Software Development Engineer II focused on building and optimizing generative AI training systems, specifically for LLMs and RL post-training pipelines, at Amazon's Stores Foundational AI team. The role involves designing scalable data infrastructure, improving training efficiency and reliability, and translating research algorithms into production-ready systems. | Post-trainData | 8 |
| Software Dev Engineer II, Stores Foundational AI -SFAI Software Development Engineer II role focused on building and improving generative AI for shopping using LLMs. Responsibilities include designing and implementing stable and efficient training systems for model training and reinforcement learning, developing scalable data infrastructure, and optimizing RL post-training pipelines. The role involves collaborating with scientists and engineers to accelerate innovation and translate research into production-ready systems. | Post-trainData | 8 |
| Software Dev Engineer II, Stores Foundational AI -SFAI Software Development Engineer II focused on building generative AI for shopping experiences at Amazon. The role involves designing and implementing stable and efficient training systems for model training and reinforcement learning, collaborating with applied scientists and engineers to improve training efficiency, and developing scalable data infrastructure for Amazon-scale data ingestion and processing across training and evaluation stages. Requires experience with ML and LLM fundamentals, transformer architecture, and training/inference lifecycles. | DataPost-train | 8 |
| Software Dev Engineer II, Stores Foundational AI -SFAI Software Development Engineer II at Amazon on the Stores Foundational AI team, focusing on building and optimizing large-scale LLM training infrastructure, including pretraining and RL post-training pipelines, data infrastructure, and observability systems for generative AI in shopping. | Post-trainData | 8 |
| Sr. Product Manager, SSC, Amazon Private Brands Product Manager role focused on AI-powered regulatory intelligence and AI agent lifecycle management within Amazon Private Brands. The role involves defining product strategy, roadmaps, and requirements for AI solutions that automate safety, sustainability, and compliance processes, aiming for autonomous operation and ensuring agents meet accuracy thresholds. | Agent | 8 |
| Sr Software Dev Engineer, Stores Foundational AI -SFAI Senior Software Development Engineer focused on building and scaling ML infrastructure for foundational LLMs in Amazon Stores, specifically involving RL post-training pipelines, stability, efficiency, and translating research into production systems. | Post-trainServe | 8 |
| Sr Applied Scientist Sr. Applied Scientist at Amazon Ring focused on computer vision and machine learning to improve customer experience and neighborhood safety. The role involves developing and deploying data-driven models, researching state-of-the-art algorithms, and collaborating with product and engineering teams. Requires experience with Multi-modal LLMs/Vision Language Models and experience in building ML models for business applications. | ShipPost-train | 8 |
| Applied Scientist II, Demand Science Applied Scientist II role focused on developing and deploying state-of-the-art ML/AI solutions for demand forecasting and supply optimization for Amazon Devices. The role involves full lifecycle ownership from research to production, including building forecasting models, exploring data, developing new approaches with AI-native experimentation and agent-driven automation, and partnering with engineering for deployment. Experience with transformer architectures, LLM-powered agents, and deep learning is required. | ShipAgent | 8 |
| Senior Manager Software Development, AWS Systems Manager Senior Manager Software Development role leading three engineering teams in AWS Systems Manager's Automation suite. The role focuses on building the execution layer for AI agents to safely take actions on cloud infrastructure at scale, including pre-execution impact analysis, safety frameworks, and intelligent orchestration. The teams will ship capabilities that enable customers to trust AI agents for autonomous operations. | AgentServe | 8 |
| Applied Scientist, AWS Applied AI Solutions Core Services This role focuses on developing and productizing AI solutions for enterprise customers within AWS Applied AI Solutions. The scientist will design and implement machine learning systems for diverse applications like video understanding, geospatial optimization, fraud detection, and anomaly detection, creating scalable algorithms and models. They will conduct experiments with LLMs, computer vision, and agentic AI systems, collaborate with engineering teams to integrate science components into production, and establish evaluation frameworks for performance measurement. The role involves working with product teams to frame problems and validate approaches, with opportunities for publication. | ShipAgent | 8 |