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, FinTelligence Senior Applied Scientist role at Amazon's FinTech organization, focusing on building and scaling generative AI applications and autonomous agents for financial operations. The role involves developing systems that process financial transactions, extract intelligence from documents, and power agents that learn from customer interactions. Key responsibilities include ensuring AI systems are trusted for compliance, designing agents that improve with user feedback, optimizing inference at scale using tiered models and LLMs, and developing robust evaluation frameworks. The position emphasizes shipping production-ready models, working across the full stack, and solving complex real-world financial problems. | AgentServe | 8 |
| Applied Science Manager, Sponsored Products and Brands Manager for the Amazon Sponsored Agent (ASA) team, focusing on building and scaling a new agentic service for conversational and agentic ads. The role involves leading a team to develop a multi-agent system architecture for contextual ad serving, conversation understanding, and commercial insights generation, with a focus on AI-native ad formats. |
| AgentServe |
| 8 |
| Senior Manager, Research Science, WW Stores Finance, WW Stores Finance This role leads the science function in WW Stores Finance, driving AI/ML innovations in financial analytics. The leader builds and directs a multidisciplinary team to deliver scalable solutions, translating AI capabilities into production systems. The role requires strategic vision and execution excellence to transform finance operations, automate workflows, and improve forecasting and controllership through agentic AI, ML, and generative AI. | AgentShip | 8 |
| Senior Manager, Science and BI Lead, WWOS Tech Senior Manager to lead an AI-first security technology organization, owning the enterprise AI/ML roadmap, leading a team of scientists and BIEs, and delivering production AI/ML models for efficiency gains and loss reduction. The role involves establishing AI/ML delivery standards, building MLOps infrastructure, and partnering with business and technical leaders, while ensuring responsible AI and compliance with regulations. | ShipServe | 8 |
| Sr. Applied Scientist, Special Projects This role is for a Sr. Applied Scientist on an Amazon Special Projects team focused on creating new products and services. The role involves leading research projects from ideation to production, driving ML/AI strategy, collaborating cross-functionally, publishing findings, and establishing best practices for ML experimentation and deployment. Requires a PhD or Master's with significant applied research experience, strong programming skills, and experience with ML/LLM fundamentals and deploying ML systems at scale. Experience with autonomous AI frameworks and translating research into production systems is preferred. | ShipServe | 8 |
| Principal Applied Scientist, Robotics This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will define the scientific roadmap for whole body control and dexterous manipulation, applying deep learning and LLMs to solve complex operational challenges in dynamic environments. The role involves research and practical implementation of AI in physical robotic hardware, with a focus on shipping these systems. | ShipAgent | 8 |
| Applied Scientist Intern This role focuses on designing and implementing innovative AI solutions, developing ML models and frameworks, enabling self-service automation, and building evaluation frameworks to enhance productivity and unlock new value within Audible. The role involves applying ML/AI approaches to solve complex real-world problems and building the blueprint for how Audible works with AI. | AgentEval Gate | 8 |
| Software Development Engineer, Applied AI Solutions Software Development Engineer role focused on building the platform for validating safety-critical autonomous systems. This involves designing scenario generation pipelines, integrating generative AI models for realistic behaviors, creating synthetic sensor data, and developing export connectors for simulation platforms. The role spans the full lifecycle from data curation to deployment monitoring, with a focus on automating testing and exploring edge cases. | DataAgent | 8 |
| Applied Scientist II - GenAI/LLM, Translation Services Applied Scientist II role at Amazon focusing on designing and developing scalable machine learning solutions for language translation services using GenAI/LLMs. The role involves applying expertise in LLM models, conducting data analysis, and collaborating with cross-functional teams to improve translation accuracy and efficiency for millions of customers worldwide. | Post-train | 8 |
| Software Development Manager, Seller Assistant, SPX Seeking a Software Development Manager to lead the development of a next-generation, GenAI-first, multi-agent system for Amazon Seller Assistant. This role involves owning end-to-end development of agentic capabilities at Amazon's scale, partnering with scientists and engineers to launch production-grade systems used by millions of sellers. | AgentShip | 8 |
| Principal Applied Scientist, Data Center Design Engineering - BIM & AI Technologies Principal Applied Scientist role focused on AI-powered design automation for AWS data centers. The role involves defining research roadmaps, developing and deploying ML models (including fine-tuning foundation models, GNNs, NLP, RL, CV) for BIM and AECO applications, and publishing research findings. It requires a blend of theoretical ML knowledge and practical application in a domain with high trust requirements. | Post-trainAgent | 8 |
| Applied Scientist, Customer360 This role focuses on researching, designing, and developing new AI technologies for personalization, leveraging LLMs, Information Retrieval, and Recommendation Systems to create unified customer understanding across Amazon's diverse businesses. The goal is to revolutionize customer experiences with AI-powered personalization and set new industry standards. | ShipAgent | 8 |
| Applied Scientist, AGI , AGI Information This role focuses on advancing knowledge graphs for the LLM era, specifically for LLM grounding and construction pipelines. It involves web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory over graphs. The primary responsibility is entity resolution for conflating facts from multiple sources into a single graph entity, requiring scalable, generic, and streaming data solutions. The role also touches upon agent memory, suggesting a secondary stage involvement. | DataAgent | 8 |
| Machine Learning Engineer, Data & Machine Learning (DML) Machine Learning Engineer on AWS Professional Services team, focusing on designing, implementing, and scaling Generative AI solutions for customers. Requires TS/SCI clearance. | AgentPost-train | 8 |
| Machine Learning Engineer , Data & Machine Learning (DML) Machine Learning Engineer to join AWS Professional Services (ProServe) team. The role involves designing, implementing, and scaling AI/ML solutions for customers, applying Generative AI algorithms to solve real-world problems, and providing expertise throughout the project lifecycle. Responsibilities include architecting solutions, selecting and fine-tuning models, developing proof-of-concepts, running experiments, and providing technical guidance on responsible AI usage. | Post-trainAgent | 8 |
| Machine Learning Engineer, Data & Machine Learning (DML) Machine Learning Engineer role focused on designing, implementing, and scaling AI/ML solutions for AWS customers. This involves selecting, fine-tuning, and deploying models, identifying use cases, and providing technical guidance on responsible AI adoption. The role requires experience with ML/statistical modeling, software engineering best practices, and a Top Secret security clearance. | AgentPost-train | 8 |
| Senior Applied Scientist, Entertainment Devices & Grocery Experiences (EDGE) Ads Senior Applied Scientist role focused on improving advertising performance and delivering innovative advertising experiences for Amazon devices and grocery. The role involves building and deploying machine learning models, with a specific emphasis on agentic AI for ads targeting, including autonomous agents, multi-agent orchestration, large multimodal models, reinforcement learning, and sequential decision making. The position requires experience in developing scalable data pipelines, optimizing conversion KPIs, and staying updated with the latest advancements in ML, NLP, and multimodal learning. | Agent | 8 |
| Applied Scientist II, Alexa International Team Applied Scientist II on the Alexa International Team at Amazon, focusing on developing novel algorithms and modeling techniques for Large Language Models (LLMs) and multimodal systems. The role involves fine-tuning/post-training LLMs, building evaluation metrics, and contributing to end-to-end delivery of solutions impacting international customers. | Post-trainAgent | 8 |
| Applied Scientist II, Alexa International Team Applied Scientist II on the Alexa International Team at Amazon, focusing on developing novel algorithms and modeling techniques for Large Language Models (LLMs) and multimodal systems. The role involves fine-tuning/post-training LLMs, building evaluation metrics, and contributing to end-to-end delivery from research to production, impacting international customers with digital assistant technology. | Post-trainAgent | 8 |
| Applied Scientist, Amazon Prime, Prime AI/ML Science Applied Scientist role focused on building and deploying AI/ML models for customer behavior prediction and personalization within Amazon Prime. The role involves working with large-scale data, leveraging GenAI, LLMs, deep learning, and reinforcement learning, and contributing to production AI/ML systems. Emphasis on scientific research, publication, and utilizing AWS technologies. | ShipAgent | 8 |
| Data Scientist, AWS Quick Data The Data Scientist II will focus on developing evaluation and benchmarking datasets for enterprise AI features, specifically for Amazon Quick Suite. This involves leveraging Generative AI techniques, LLMs for synthetic data generation, and LLM-as-a-judge settings to assess model performance, ensure data quality, and contribute to Responsible AI initiatives. The role also includes building scalable data pipelines and tools for continuous evaluation. | Eval GateData | 8 |
| Sr. Software Development Manager, MHLS Tech This role manages multiple engineering teams responsible for building and scaling AI-powered conversational systems, knowledge management platforms, and intelligent routing solutions for Amazon's global employee support platform. The focus is on defining and executing the AI/ML strategy for production generative AI systems, including LLMs and agentic frameworks, while ensuring scalability, reliability, and responsible AI practices. | AgentServe | 8 |
| Applied Scientist , Amazon Customer Service Applied Scientist II role focused on building AI-based automated customer service solutions using RAG, agentic AI, and post-training of LLMs. Responsibilities include designing and deploying RAG pipelines, conducting LLM post-training, curating datasets, implementing evaluation frameworks, developing AI agents, and collaborating with cross-functional teams. The role involves research and development with minimal guidance, aiming to translate research into production systems and contribute to the scientific community. | AgentPost-train | 8 |
| 2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - United States, PhD Student Science Recruiting This internship focuses on developing systems and frameworks for machine learning asset lifecycle management, leveraging NLP and information retrieval. The role involves research into ML operations and knowledge engineering to enhance Amazon's ML capabilities. | DataPost-train | 8 |
| 2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting This internship focuses on research in Reinforcement Learning and Optimization within Machine Learning, developing and implementing novel algorithms for complex real-world challenges. The role involves working with large-scale data and applying cutting-edge ML techniques. | Post-train | 8 |
| Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect This role focuses on accelerating customer adoption of Amazon Connect's AI capabilities by acting as an Applied AI Solutions Architect. The architect will guide customers in selecting foundation models, designing and optimizing AI prompts, and architecting tool integrations for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and helping customers move from proof-of-concept to pre-production for Amazon Connect + Unlimited AI deployments. The role involves hands-on coding, building integrations, configuring agents, and collaborating with customer engineering teams. | Agent | 8 |
| Applied Scientist, Mobile Manipulation Robotics (I/O) Applied Scientist focused on developing learning-based approaches for mobile manipulation in robotics, aiming to advance capabilities for robots navigating and manipulating objects in dynamic fulfillment environments. The role involves model development, training, data management, experimentation, validation, and code development for production systems at Amazon's scale. | ShipData | 8 |
| Applied Scientist, AGI Customization Services Applied Scientist role focused on developing and customizing large language models for enterprise use cases, involving techniques like supervised fine-tuning, reinforcement learning, and knowledge distillation. The role requires building enterprise-ready tooling, optimizing models, and contributing to responsible AI toolkits. | Post-trainData | 8 |
| 2026 Fall Applied Science Internship - Recommender Systems/ Information Retrieval (Machine Learning) - United States, PhD Student Science Recruiting This internship focuses on developing and evaluating new recommendation and search algorithms, building data processing pipelines, and conducting research in recommender systems and information retrieval. The role involves applying machine learning, deep learning, and NLP techniques to large-scale datasets to improve personalized experiences for Amazon customers. | ShipData | 8 |
| 2026 Fall Applied Science Internship - Computer Vision - United States, PhD Student Science Recruiting This internship focuses on developing and implementing cutting-edge computer vision algorithms and models for Amazon's consumer-facing products and services, such as Rekognition, Go, and Visual Search. The role involves working with large-scale systems, including mobile robots and advanced tooling, to solve real-world problems. Interns will contribute to production-level projects, technical white papers, and roadmaps, with a strong emphasis on applied science and deep learning in computer vision, potentially involving Vision-Language Models and LLMs. | ShipAgent | 8 |
| Applied Scientist , AWS Healthcare-AI Senior Applied Scientist role at AWS Healthcare AI, focusing on developing and researching AI-driven clinical solutions to transform healthcare delivery. The role involves defining research directions, developing new ML techniques, and ensuring research translates into impactful products for clinicians and patients. Requires a PhD or Master's with significant experience in ML, NLU, deep learning, foundation models, and RL, with a strong publication record. | ShipPost-train | 8 |
| Principal Applied Scientist, Prime Video Personalization & Discovery Principal Applied Scientist role at Prime Video focused on inventing, developing, and deploying AI solutions for personalization and discovery. The role involves technical and strategic leadership, guiding ML systems from research to production, and mentoring scientists. Key responsibilities include prototyping and productionizing large-scale AI solutions using deep learning, generative AI, RL, and optimization, providing technical leadership, designing A/B tests, driving technical bar-raising, and staying ahead of industry trends. The team focuses on creating a highly personalized content discovery experience using ML and Generative AI. | ShipPost-train | 8 |
| Senior Machine Learning Engineer, AWS Identity Analytics Platform Senior Machine Learning Engineer at AWS Identity Analytics Platform, focusing on building an AI-driven analytics platform that processes petabyte-scale data to generate insights for security and operational problems. The role involves designing, developing, and deploying ML solutions, including anomaly detection, time-series forecasting, classification, optimization models, and LLM-powered agents for conversational data querying. It also includes feature engineering, production deployment, and collaboration with leadership and service teams. | AgentData | 8 |
| Senior Economist, SEI Science Team Senior Economist to define and build GenAI-first, multi-agent systems for Amazon Seller Assistant, owning capabilities end-to-end from insight to shipped product. Focus on agentic experiences, translating research into production, and designing evaluation frameworks. | Agent | 8 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science This role focuses on developing and launching end-to-end AI solutions for Prime Video's recommendation and personalization systems. It involves deep learning, GenAI, reinforcement learning, and optimization methods, with a strong emphasis on experimental design (A/B testing) and research publication. The scientist will work closely with engineers and product managers to bring these solutions to millions of customers. | Ship | 8 |
| Senior Applied AI Solutions Architect — Amazon Connect Senior Applied AI Solutions Architect for Amazon Connect, focused on accelerating customer adoption of AI capabilities. The role involves guiding customers in model selection, prompt configuration, and tool integration for AI agents, with a strong emphasis on customer data readiness and enabling multi-agent orchestration. This is a hands-on role requiring coding, integration building, and pair-programming with customer teams to move from proof-of-concept to production. | Agent | 8 |
| Senior ML Engineer, Fauna Senior ML Engineer to build and scale ML systems for intelligent robots, focusing on designing and maintaining infrastructure for training, evaluating, and deploying ML models. The role involves working at the intersection of ML and systems engineering to ensure robust, efficient, and scalable systems, with a focus on optimizing model inference for edge devices. | ServeData | 8 |
| Applied Science Manager GenAI, CreativeX, Amazon Advertising Manager for a team of applied scientists and ML engineers focused on building generative AI solutions for advertisers within Amazon Advertising. The role involves setting scientific strategy, mentoring scientists, managing talent, and delivering AI products at scale, with a focus on multi-modal generative AI for creative assets. | Ship | 8 |
| Senior AI Architect, Agentic AI Professional Services Experience Senior AI Architect role focused on designing and building AI agents for AWS Professional Services to automate and accelerate consulting services delivery. The role involves working with customers, leading technical solutions, and architecting scalable AI/ML and GenAI solutions on AWS. | Agent | 8 |
| Sr. Applied Science Manager, AGI Information This role leads teams of applied scientists and ML engineers to develop and deliver AI systems for Amazon businesses, focusing on integrating information into AI systems using techniques like RAG. The role involves defining technical roadmaps, mentoring teams, and driving research from conception to production, with a strong emphasis on building impactful AI-driven products and services. | Ship | 8 |
| Data Scientist, AWS Quick Data The Data Scientist will focus on developing evaluation and benchmarking datasets for generative AI capabilities within the Amazon Quick Suite enterprise AI platform. This includes leveraging LLMs for synthetic data generation, creating ground truth datasets, leading human annotation initiatives, and contributing to Responsible AI efforts to ensure enterprise-readiness, safety, and effectiveness of AI at scale. | Eval GateData | 8 |
| Machine Learning Engineer, Alexa AI Machine Learning Engineer for Alexa AI focused on LLM training, production deployment, and inference optimizations. Will collaborate with Applied Scientists and other MLEs to leverage Amazon's data and computing resources for Generative AI solutions. Responsibilities include investigating design approaches, prototyping, evaluating technical feasibility, processing data, scaling ML models, and delivering high-quality software in an Agile environment. Experience with PyTorch/JAX, vLLM, SGLang, TensorRT, and developing large model hosting platforms is preferred. | ServePost-train | 8 |
| Senior Applied Scientist, Industrial Robotics Group Senior Applied Scientist role focused on developing AI and ML systems for industrial robotics and manufacturing, involving real-time decision making, optimization, and inventing new algorithms. The role requires delivering complex solutions into production and has a strong emphasis on scientific code development and evaluation. | ShipData | 8 |
| Senior Product Manger - Tech, Infrastructure Reliability Product Manager for an AI-powered infrastructure reliability platform that uses LLMs and multi-agent systems to prevent, detect, and resolve incidents in Amazon's fulfillment network. The role involves defining product roadmaps, writing code for proof-of-concepts, and collaborating with data scientists and engineers on ML model applications, agent architecture, and evaluation frameworks. | AgentEval Gate | 8 |
| Senior Manager, AI Red Team, Threat Operations Senior Manager to lead an AI Red Team focused on security research and offensive operations targeting AI systems, infrastructure, and emerging threats. The role involves building and leading a team, establishing the AI offensive security research program, driving Red Team operations, and partnering with stakeholders to protect AI offerings and customer trust. | ServeData | 8 |
| Applied Scientist, Grocery, Retail & In-Store Experience (GRAISE) Applied Scientist role focused on designing, developing, and deploying machine learning and computer vision models for Amazon's in-store grocery technologies. The role involves end-to-end model development, from ideation to production, with a focus on solving complex grocery-domain problems at scale and improving the customer shopping experience. | ShipServe | 8 |
| Software Development Manager - AWS Glue, Glue and GenAI for Data Processing Software Development Manager to lead a team building agentic AI systems for AWS Glue, EMR, and Athena, focusing on automated Spark upgrade and migration agents, and a managed analytics service providing AI assistants and agents access to tools. The role involves owning design, implementation, testing, and deployment, driving technical decisions at the intersection of GenAI, distributed systems, big data, and ML, and partnering with senior leadership and customers. | Agent | 8 |
| ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs The role focuses on optimizing ML kernel performance for AWS Neuron SDK on custom ML accelerators (Inferentia and Trainium). It involves designing and implementing high-performance compute kernels, analyzing and optimizing kernel-level performance, implementing compiler optimizations, and collaborating with customers and internal teams to enable and optimize ML models. The work is at the hardware-software boundary, combining deep hardware knowledge with ML expertise. | Serve | 8 |
| Software Engineer II- AI/ML, AWS Neuron Software Engineer II role focused on optimizing and enabling deep learning and GenAI workloads on AWS custom ML accelerators (Inferentia and Trainium) by developing and enhancing the AWS Neuron SDK. This involves working across the stack from frameworks like PyTorch/JAX to hardware-software boundaries, optimizing ML compilers, runtimes, and high-performance kernels for inference and training. The role requires strong software development skills in Python/C++, system-level programming, ML knowledge, and collaboration with various teams to ensure optimal performance for customers. | ServePost-train | 8 |
| Principal GenAI Specialist SA This role is for a Principal GenAI Specialist SA at Amazon, focusing on designing and architecting scalable, secure, and cost-effective AI/ML, Generative AI, and Agentic AI solutions on AWS. The role involves guiding customers through their AI transformation, establishing GenAIOps practices, and creating enterprise-grade AI architectures. It requires deep technical experience across the AI spectrum, including LLM customization/fine-tuning, inference optimization, agentic frameworks, GenAIOps, security, RAG systems, and prompt engineering. | Agent | 8 |
