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 II, Trustworthy Shopping Experience (TSE) Applied Scientist II on Amazon's Trustworthy Shopping Experience (TSE) team, focusing on building and productionizing generative AI solutions for automating complex manual investigation processes at scale. The role involves designing and building agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence, leveraging techniques like SFT, RFT, and few-shot approaches. The scientist will also work on prompt optimization, novel Finetuned transformer architectures, and identifying business problems to apply state-of-the-art LLM workflows. The role offers end-to-end ownership from research to production deployment, with a focus on impacting cost-of-serving customers while maintaining trust and safety. | AgentPost-train | 8 |
| Applied Science Manager, Personalization |
| Agent |
| 8 |
| Applied Scientist, Personalization, Personalization Seeking an Applied Scientist to build Amazon's next-generation customer memory and personalization systems. This role involves designing and building ML and LLM-powered solutions for extracting, curating, and reasoning over customer knowledge to power personalization. The work spans information extraction, knowledge representation, LLM reasoning, and recommendation systems, operating under real-world constraints of scale, latency, and quality. The scientist will own end-to-end delivery from problem formulation to production deployment. | AgentData | 8 |
| Applied Scientist, Personalization, Personalization Seeking an Applied Scientist to build Amazon's next-generation customer memory and personalization systems. This role involves designing and building ML and LLM-powered solutions for extracting, curating, and reasoning over customer knowledge to power personalization. The work spans information extraction, knowledge representation, LLM reasoning, and recommendation systems, operating under real-world constraints of scale, latency, and quality. The scientist will own end-to-end delivery from problem formulation to production deployment. | AgentData | 8 |
| Principal Solutions Architect, AWS Financial Services, Industry Specialists for Capital Markets Principal Solutions Architect for AWS Financial Services, specializing in Capital Markets. This role focuses on designing and architecting AWS solutions for clients in hedge funds, asset management, and quantitative trading firms, with a strong emphasis on data and analytics, generative AI, and high-performance computing. Responsibilities include migrating data-intensive workloads, architecting generative AI/ML solutions (LLM fine-tuning, RAG, sentiment analysis, agentic AI), and designing HPC environments. The role involves deep technical expertise and customer engagement to accelerate modernization on AWS. | AgentData | 8 |
| Senior Applied Scientist, Sponsored Products and Brands Senior Applied Scientist role focused on architecting and pioneering applied science in multi-modal Generative AI for Amazon's Sponsored Products and Brands advertising platform. The role involves end-to-end innovation from research to production deployment at Amazon scale, with a focus on non-US marketplaces and leveraging technologies like LLMs and semantic hash designs. The candidate should have experience building ML models, deep technical expertise, and a proven track record of delivering value with state-of-the-art technologies in production environments. | ShipAgent | 8 |
| Senior Software Engineer (ML), Data Plane Senior Software Engineer focused on optimizing the ML inference data plane for custom hardware, involving compute kernels, serving integration, and end-to-end model execution for large distributed models. | Serve | 8 |
| Sr. Applied Scientist, Alexa Excellence AI Ops, Alexa Excellence AI Ops Senior Applied Scientist role focused on developing and deploying ML and statistical models for Alexa's reliability at scale. This involves time series analysis, anomaly detection, LLM-driven operational intelligence, and adaptive thresholds, with a focus on production-grade solutions and rigorous evaluation. | AgentData | 8 |
| Applied Science Manager, AWS Generative AI Innovation Center Manager for an AWS Generative AI Innovation Center focused on building and deploying generative AI solutions for customers, managing a team of scientists and engineers, and driving adoption of AI technologies. | ShipPost-train | 8 |
| Applied Scientist II, Sheriff Team- Payroll tech This role focuses on developing and maintaining ML and Generative AI applications for Payroll Operations at Amazon. Key responsibilities include inventing, implementing, and influencing ML/GenAI capabilities for anomaly detection, sentiment analysis, ticket classification, virtual assistance, and automated policy extraction. The role involves driving model accuracy, scientific innovation, and global scale, with a focus on integrating ML components into production systems and influencing strategic planning for AI capabilities. | AgentPost-train | 8 |
| Senior Applied Scientist, Leo Satellite Build Intelligence Senior Applied Scientist to lead the development of AI models for satellite manufacturing, transforming data into an intelligence system that improves how satellites are built. Focuses on AI-native workflows like non-conformance disposition, root-cause analysis, and predictive test optimization, influencing real-world manufacturing decisions. | AgentData | 8 |
| Senior Manager, Applied Science, Prime Video Advertising Senior Manager, Applied Science at Amazon Prime Video Advertising, leading a team to build and scale ML/AI solutions for advertising optimization, experimentation, and generative AI-powered ad creative generation. The role involves setting scientific vision, managing managers, and driving strategic initiatives in a rapidly growing business. | Ship | 8 |
| Applied Scientist I, Alexa Ads Applied Scientist role focused on building Generative AI models for conversational ads and personalization within the Alexa ecosystem. The role involves designing, developing, and evaluating deep learning models for NLP and recommendation systems, building ML pipelines, running A/B experiments, and deploying models to production. The team is greenfield, aiming for direct business impact and encouraging top-tier publications alongside production deployment. | AgentEval Gate | 8 |
| Senior Applied Scientist, Alexa Ads Senior Applied Scientist role focused on building Generative AI models for conversational ads and personalization within the Alexa ecosystem. The role involves designing, developing, and evaluating deep learning and GenAI models, conducting data analysis, building ML pipelines, running A/B experiments, and collaborating with engineers for production deployment. The team is greenfield, aiming for direct business impact and encouraging both production deployment and top-tier publications. | ShipAgent | 8 |
| Generative AI Solutions Architect, AWS Global Government Specialist SA This role focuses on designing and implementing generative AI solutions for government customers using AWS services. The Solutions Architect will act as a Subject Matter Expert, guiding customers and internal teams on leveraging AI for automation and cost reduction. The role requires deep technical experience in AI/ML and integrating these services into production applications. | Ship | 8 |
| Generative AI Solutions Architect, AWS Global Government Specialist SA This role focuses on designing and implementing generative AI solutions for government customers using AWS services. The Solutions Architect will act as a Subject Matter Expert, guiding customers and internal teams on leveraging AI for automation and cost reduction. The role requires deep technical experience in AI/ML and integrating these services into production applications. | Ship | 8 |
| Senior Data Scientist , Alexa AI Aurora Senior Data Scientist role focused on conversational AI, LLMs, NLP, and Generative AI for Alexa. The role involves defining strategy, leading initiatives from problem formulation to production, establishing evaluation frameworks, and driving consensus on agentic systems. It requires expertise in machine learning, generative AI, and computer vision, with a focus on delivering scalable and impactful solutions for millions of customers. | AgentPost-train | 8 |
| Applied Scientist II, Amazon Travel & Events Applied Scientist II role focused on building AI-driven solutions for Amazon Travel & Events, leveraging Generative AI, LLMs, NLU, conversational AI, and Applied ML. Responsibilities include designing, developing, and evaluating ML models using GenAI, multimodal reasoning, and information retrieval for catalog understanding, applying VLMs and LLM-based approaches with fine-tuning and RAG, implementing model optimization techniques for efficiency, driving experiments, building ML pipelines, contributing to model reliability through interpretability and calibration, and collaborating with teams to translate business requirements into ML solutions. The role also involves staying current with research and co-authoring publications. | AgentServe | 8 |
| Sr Applied Scientist - Robotics Simulation, Amazon Robotics R&D Senior Applied Scientist role focused on developing 3D physics-based simulation environments and tools for robotics, specifically for training large-scale machine learning models using reinforcement learning and synthetic data generation. The role involves establishing processes, building real-to-sim workflows, and minimizing sim-to-real gaps, with a secondary focus on enabling agentic systems through simulation. | DataAgent | 8 |
| Applied Scientist, EU INTech Consumer Selection Discovery, EU InTech Consumer Selection Discovery Amazon is seeking Applied Scientists to build software and machine learning models for customer discovery experiences, focusing on ranking, recommendations, and computer vision. The role involves developing and deploying state-of-the-art models, including text-to-image and image-to-text, to enhance customer engagement with the Amazon catalog. | Ship | 8 |
| Software Development Engineer - AI/ML, Amazon Neuron, Multimodal Inference Software Development Engineer focused on optimizing and accelerating deep learning and GenAI workloads on AWS's custom ML accelerators (Inferentia and Trainium) through the AWS Neuron SDK. This role involves architecting, implementing, and tuning distributed inference solutions, focusing on performance optimization (latency and throughput) from system level to framework level (PyTorch, JAX). The engineer will work on low-level optimizations, system architecture, and ML model acceleration, collaborating across hardware, compiler, runtime, and framework teams. | Serve | 8 |
| Data Scientist II, Central Seller Fulfillment Data Scientist II role focused on building and productionizing personalized Gen AI systems for Amazon's global selling partners, with a focus on Agentic, RL, and forecasting products. Requires expertise in ML/DL frameworks, agentic frameworks, and experience with complex AI systems and data pipelines. | AgentShip | 8 |
| Principal Applied Scientist, Sponsored Products and Brands The Principal Applied Scientist will lead the development and deployment of generative AI technologies for Amazon Ads, specifically within the Sponsored Products and Brands team. This role involves reinventing advertising experiences by integrating AI into the ad lifecycle, from creation to performance analysis. The scientist will invent new product experiences, bring state-of-the-art GenAI models to production, and define the long-term science vision for the advertising business, collaborating closely with science, product, and engineering teams to deliver high-impact products. | Ship | 8 |
| Principal Applied Scientist, Amazon Payments Principal Applied Scientist for Amazon Payments AI/ML Team, focusing on AI services for payments, recommendation, prediction, and GenAI for SOP automation. The role involves setting AI direction, mentoring scientists, partnering with engineering to deliver ML/GenAI features, identifying research directions, creating roadmaps, and bringing research to production. Requires a PhD or MSc with 10+ years of experience, a track record of thought leadership, and strong collaboration skills. | Ship | 8 |
| Senior Security Engineer, AI Red Team, Threat Operations Senior Security Engineer focused on offensive security operations and research for AI systems, including training pipelines, inference systems, and model architectures. The role involves discovering and exploiting vulnerabilities, developing automation for threat emulation, and collaborating with engineering teams to improve AI security posture. | Agent | 8 |
| Applied Scientist, Customer Behavior Analytics Scientist role focused on designing and developing machine learning solutions for customer behavior analytics, utilizing deep learning, LLMs, recommendation systems, and reinforcement learning. Key responsibilities include fine-tuning generative models, developing recommendation and decision models, building behavioral representations, applying post-training optimization, and creating evaluation frameworks. The role emphasizes measurable business impact and customer satisfaction. | Post-trainAgent | 8 |
| Data Scientist II, Enterprise Security Products Data Scientist II role focused on building AI-first security products, including agentic systems, anomaly detection, and threat classification. The role involves the full ML lifecycle, from problem framing to production deployment and monitoring, with an emphasis on using AI tools to accelerate development. Key responsibilities include powering agentic architectures with models, embeddings, RAG pipelines, and evaluation frameworks, rapid prototyping, and customer validation. The role also involves partnering across disciplines and communicating complex results. The team operates with startup speed at Amazon scale, emphasizing rapid iteration and shipping. | AgentData | 8 |
| Senior Applied Scientist, AWS Security Senior Applied Scientist role focused on building AI-powered tooling for AWS Security operations, including generative AI incident response assistants, natural language-driven response, detection enrichment pipelines, and security data analytics platforms. The role involves defining and executing the ML/AI roadmap, extending and inventing techniques at the product level, and bringing models from research into production systems. Responsibilities include LLM-powered incident triage, anomaly detection, RAG, prompt engineering, fine-tuning, developing evaluation frameworks, and mentoring engineers. | AgentServe | 8 |
| Applied Scientist, AWS Marketplace & Partner Services Applied Scientist at AWS Marketplace focused on building and improving AI/ML-powered discovery systems. The role involves developing models for search ranking, query understanding, and recommendations, and extending these into agentic discovery experiences using multi-agent systems. Collaboration with engineers and product managers to deploy solutions into production is key. | AgentServe | 8 |
| Director of Science, Geospatial Director of Science, Geospatial at Amazon, leading a team of ~50 scientists focused on AI/ML solutions for last-mile delivery operations. The role involves developing and deploying solutions for geospatial problems, including address validation, place datasets, road networks, and leveraging edge data. Key focus areas include GenAI (LLMs, VLMs, agents), computer vision, and traditional ML to optimize delivery routes, improve data fidelity, and drive business impact. The role requires interfacing with senior stakeholders, strategic planning, and building a high-performing team. | ShipAgent | 8 |
| Customer Solutions Manager, Prototyping & Customer Engineering This role focuses on managing AI-focused customer engagements end-to-end, partnering with engineers and designers to deliver AI solutions using technologies like LLMs, RAG, and autonomous agents. The role involves orchestrating customer engagements, facilitating solution design, identifying opportunities, building relationships, and ensuring responsible AI practices. | Agent | 8 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science Sr. Applied Scientist at Amazon Prime Video focused on developing and launching AI solutions for personalization and discovery systems, impacting millions of customers. | Ship | 8 |
| Sr. Applied Scientist – AI Velocity Team, Applied AI Acceleration Solutions Architecture Senior Applied Scientist role focused on developing and deploying AI/ML models and analytics for customer-facing AI solutions within Amazon Connect. The role involves working directly with customers to accelerate production deployments, designing and building AI solutions, conducting experiments, quantifying business value, and applying NLP/generative AI techniques. It spans conversational analytics and agentic AI capabilities, with a strong emphasis on driving measurable business impact and operational excellence in customer environments. | ShipAgent | 8 |
| Applied Science Manager - Match & Affordances, Amazon Robotics This role manages a team of applied scientists and engineers focused on developing ML and RL algorithms for robotic systems to optimize stow strategy and warehouse capacity. It involves leading research, design, deployment, and evaluation of these systems, with a focus on transformer architectures, affordance learning, and geometric reasoning in high-density environments. | AgentData | 8 |
| Manager, Applied Science, Alexa AI Manager for an Applied Science team focused on LLM-powered conversational AI for Alexa, encompassing agent execution, understanding, reasoning, evaluation, and runtime systems. The role involves leading scientists, developing platforms, driving innovation, and collaborating across functions to deliver scalable production solutions and advance research. | AgentEval Gate | 8 |
| Applied Scientist, Central Seller Fulfillment Machine Learning Scientist role focused on building and productionizing personalized Gen AI systems for Amazon's global selling partners, with a focus on Agentic, RL, or forecasting systems. Requires expertise in deep learning frameworks, agentic frameworks, and scalable AI system design. | Agent | 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 |
| Senior Applied AI Solutions Architect, Federal Financial Senior Applied AI Solutions Architect for Federal Financial Regulatory customers, focusing on designing and enabling AI/ML solutions for fraud detection, market surveillance, regulatory reporting, and consumer protection. The role involves technical guidance, developing reference architectures, and enabling customer adoption of AI/ML on AWS, with a strong emphasis on agentic systems and RAG. | Agent | 8 |
| 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 |
| Deep Learning Architect, AWS Gen AI Innovation Center This role involves designing, implementing, and fine-tuning state-of-the-art Generative AI solutions for AWS customers, focusing on real-world problem-solving and production deployment. The architect will collaborate with customers and internal teams to understand business needs, develop proof-of-concepts, and guide adoption patterns. | AgentPost-train | 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 |
| 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 |
| 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, 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 |