Currently tracking 1110 active AI roles, down 11% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
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.
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, GenAI Evaluation Media Applied Scientist role focused on Generative AI for visual media, specifically in 3D Generative AI and Inverse Rendering. The role involves building scalable CVML models, automating their application, and designing/building pipelines to train and deploy ML models. Expertise in areas like Neural Fields, NeRFs, GANs, Diffusion Models, and differentiable rendering is required. The role bridges computer graphics, computer vision, and deep learning to improve customer experience with product imagery and videos. | Post-trainServe | 8 |
| Applied Scientist II, Brand Registry The Applied Scientist II role on the Brand Registry team at Amazon focuses on designing, developing, and deploying AI solutions, specifically leveraging LLMs and agentic AI frameworks to create intelligent automation and autonomous outcomes for brand protection and seller experience. The role involves owning the end-to-end ML lifecycle, from problem formulation to production deployment, and collaborating with product managers and engineering teams. |
| Agent |
| 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 |
| Applied Scientist, Amazon Compliance and Safety Services Applied Scientist role focused on researching and developing NLP, multi-modal, and LLM-based ML solutions for product compliance and safety within Amazon. The role involves evaluating existing algorithms, designing new ones, generating synthetic data, and potentially using active learning and grounding LLMs for business use cases. Collaboration with engineers and product managers is key, with an emphasis on publishing research. | Post-trainData | 8 |
| Sr. Machine Learning Compiler Engineer, AWS Neuron, Annapurna Labs This role focuses on developing and scaling a machine learning compiler for AWS Neuron, which optimizes the performance of neural network models on custom AWS hardware accelerators (Inferentia and Trainium). The engineer will architect and implement features for the compiler stack, which integrates with popular ML frameworks, aiming to improve inference and training performance for large ML workloads. | Serve | 8 |
| Director Product Management-Technical, Amazon Customer Service Director of Product Management, Technical, focusing on Data & Context Intelligence within Amazon Customer Service. The role involves redefining customer experiences through AI-native products, leading cross-functional teams, and building scalable AI solutions including agentic AI, generative AI, and multi-agent architectures. Key responsibilities include defining product vision, making technical decisions, building and scaling AI-native solutions, defining technical direction for agentic AI, driving cross-functional alignment, and building a high-performing organization. | Agent | 8 |
| Applied Scientist II, Prime Video - Personalization and Discovery Science This role focuses on developing and applying ML models, including foundation models, for recommendation and search systems within Prime Video's personalization and discovery science team. The goal is to enhance customer experience by recommending titles effectively and enabling discovery of niche interests. The role involves end-to-end ownership, experimentation, and collaboration with scientists, engineers, and product managers, with an emphasis on publishing research findings. | Ship | 8 |
| Principal Software Engineer, Agentic AI DevOps This Principal Software Engineer role focuses on building agentic AI solutions for AWS DevOps, aiming to accelerate incident response and improve operational efficiency for production systems. The role involves working with information retrieval systems, knowledge graphs, and LLMs to create a frontier agent that resolves incidents and learns from them for systemic improvements. | Agent | 8 |
| Applied Scientist II, RBS Tech The Applied Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience (CX) and Selling Partner experience (SPX). The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques for task automation, text and image processing, pattern recognition, and anomaly detection. It also includes defining research strategies, partnering with business and engineering teams, and potentially filing patents or publishing research. | AgentPost-train | 8 |
| Applied Scientist II, RBS Tech The Applied Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience (CX) and Selling Partner experience (SPX). The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques for task automation, text and image processing, pattern recognition, and anomaly detection. It also includes defining research strategies, partnering with business and engineering teams, and potentially filing patents or publishing research. | AgentPost-train | 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 |
| Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect Sr. Applied AI Solutions Architect focused on accelerating customer adoption of Amazon Connect's AI capabilities. The role involves guiding customers in model selection (via Amazon Bedrock), prompt configuration for AI agents, and architecting tool integrations (APIs, Lambda, etc.) for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and RAG. The role is hands-on, requiring coding, building integrations, and configuring agents, working at the intersection of contact center operations and applied AI. | Agent | 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 |
| Applied Scientist II, Prime Video Personalization and Discovery Science Applied Scientist II at Amazon Prime Video focusing on personalization and discovery. The role involves developing foundation models for content understanding (video, text) and customer behavior prediction using deep learning and multimodal techniques. Responsibilities include building time sequence models, end-to-end solution implementation with engineers and product managers, designing and conducting A/B experiments, and publishing research findings. The team works on recommendation science for Prime Video surfaces and devices, aiming to solve cold-start problems and discover niche customer interests. | Post-trainAgent | 8 |
| Applied Scientist II, Prime Video - Personalization and Discovery Science This role focuses on developing and applying ML models, including foundation models, for recommendation and search systems within Prime Video's personalization and discovery science team. The goal is to enhance customer experience by recommending titles effectively and enabling discovery of niche interests. The role involves end-to-end ownership, experimentation, and collaboration with scientists, engineers, and product managers, with an emphasis on publishing research findings. | Ship | 8 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science Senior Applied Scientist role focused on developing and launching foundation models for content understanding and customer behavior prediction within Prime Video. The role involves hands-on machine learning, research leadership, and end-to-end ownership of solutions, with an emphasis on publishing research findings. | Post-trainAgent | 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 Scientist II, Amazon Connect Research and develop generative AI technology for Amazon Connect, focusing on LLM Agents and their evaluation/optimization to disrupt customer service experiences. The role involves building ML models from conception to deployment, prototyping, and iterating on state-of-the-art Agentic AI systems. | AgentPost-train | 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 |
| Senior Software Development Engineer - AI Mftg & Automation, Advanced Manufacturing Engineering (AME) Senior Software Development Engineer to lead AI/ML/LLM/VLM/VLA development for automating manufacturing engineering workflows, including agentic AI, robotic control, and computer vision for quality assurance. | AgentServe | 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, Sponsored Products Off-Search Homepage Team This role focuses on applying Generative AI and LLMs to transform ad experiences on Amazon's homepage and other surfaces, impacting product discovery and customer engagement. It involves building and deploying models for ad retrieval, auctions, and personalized shopping experiences, operating across the full stack from backend systems to the user-facing layer. | ShipAgent | 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 |
| Applied Scientist-LLM, Buy For Me Seeking an Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to build LLM-powered solutions for Amazon's BuyForMe product. The role involves developing agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve shopping workflows. | AgentPost-train | 8 |
| Senior Applied Scientist, Last Mile Delivery Senior Applied Scientist role focused on developing computer vision and perception systems for AI agents in last-mile delivery logistics. The role involves designing and implementing deep learning models for visual perception, building algorithms for decision-making, and creating robust systems for AI agents to operate safely in complex environments. It spans from object detection and tracking to path planning and control, including sim-to-real transfer and continuous learning from agent experiences. | AgentServe | 8 |
| Applied Scientist II The role focuses on developing and applying cutting-edge simulation methodologies for advanced robotics systems, including physics-based simulation, sim-to-real transfer, and machine learning. The goal is to enable rapid development, testing, and validation of robotic systems in complex environments. The role involves fundamental research and real-world development, translating research into scalable simulation capabilities that impact robot design and building. | DataAgent | 8 |
| Applied Scientist II, Reinforcement Learning Applied Scientist II role focused on developing advanced robotics systems using AI, deep learning, and reinforcement learning for automation at Amazon's scale. The role involves designing and implementing control methods for balance, locomotion, and manipulation, with a focus on bridging theoretical advancements and practical implementation in robotics. | Ship | 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 |
| Principal Applied Scientist, PXT This role leads the science strategy and technical vision for an intelligence layer using GenAI and predictive modeling, focusing on heterogeneous signals to power talent applications at Amazon scale. The Principal Applied Scientist will guide a team, conduct hands-on research in areas like foundation models and multi-modal LLMs, design novel ML architectures, and mentor scientists while contributing technically to complex problems. | Post-trainAgent | 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 |
| Applied Science Manager, AWS Generative AI Innovation Center Manager for an AWS Generative AI Innovation Center focused on building and delivering generative AI solutions for customers, managing a team of scientists and engineers, and driving adoption and strategic relationships. | ShipPost-train | 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 |
| Applied Scientist II, Amazon Business, Amazon Business - GTMO Science Applied Scientist II role at Amazon Business focused on revolutionizing sales productivity using AI-powered solutions. The role involves developing tools for Account Executives (AEs) to prioritize accounts, recommend products, and engage customers more effectively. It leverages machine learning and Generative AI to outreach customers based on their behavior and purchase history, and performs text mining on customer conversations to recommend solutions. The scientist will partner with product, tech, and sales teams to launch and scale global AI products, with a focus on improving customer experience and sales efficiency. | AgentData | 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 |
| Sr. Prototyping Architect, PACE, AWS Prototyping and AI Customer Engineering (PACE) Sr. Prototyping Architect for AWS PACE team, building functional Generative AI and Agentic AI prototypes with customers using AWS AI services. Focus on architecting, developing, and guiding customers through complex technical decisions on LLMs, agent design patterns, and AI adoption strategies, with a path to production. | Agent | 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 |