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 |
|---|---|---|
| Postdoctoral Researcher – Visual Localization & Navigation | Amazon Last Mile Research scientist role focused on visual localization and navigation for robotics and logistics platforms, involving metric-semantic mapping, relocalization, and monocular localization using geometric and learning-based approaches. | Agent | 8 |
| Applied Scientist, Prime Video Commerce Insights Applied Scientist role focused on Reinforcement Learning and ML for personalization in Prime Video Commerce, involving research, design, implementation, and deployment of recommendation systems at scale with low latency. The role aims to improve customer experience and business metrics by applying advanced ML techniques and contributing to the science roadmap. | AgentServe |
| 8 |
| Applied Scientist II, Demand Enablement, Product Analytics and Operations This role focuses on designing and building intelligent multi-agent systems for automating root cause analysis in advertising campaign delivery at scale. It involves architecting agentic orchestration, developing hierarchical analysis frameworks, and creating self-learning feedback loops. The goal is to significantly reduce advertiser escalation time by leveraging LLM-based agent architectures and retrieval-augmented generation. | Agent | 8 |
| Solutions Architect III, HCLS AI/ML and Data Strategy Specialists, Global Healthcare Solutions Architect III for AWS Healthcare & Life Sciences, focusing on architecting production AI/ML systems, including generative AI and agentic architectures, for healthcare organizations. The role involves leading technical engagements, defining reference architectures, influencing stakeholders, and producing thought leadership content, with a strong emphasis on regulated environments. | AgentData | 8 |
| Public Sector Partner SA - OpenAI , WWPS Global ISV Partners This role focuses on being a technical partner lead for OpenAI within AWS's public sector, designing, prototyping, and deploying generative AI solutions. It requires hands-on engineering skills to build prototypes, evangelize capabilities, publish reference architectures, and work with both developers and executives in regulated and classified environments. The role involves deep collaboration with OpenAI and government customers, focusing on RAG, agentic workflows, fine-tuning, and multi-modal deployments on AWS. | AgentServe | 8 |
| Applied Scientist, Prime Video Commerce Insights Applied Scientist role focused on building and deploying ML-driven personalization and recommendation systems for Prime Video's commerce journey. The role involves researching, designing, and implementing models at scale, collaborating with engineers for production deployment, and contributing to the science roadmap with a focus on reinforcement learning and customer behavior. | AgentServe | 8 |
| Sr Software Development Engineer, Sponsored Products and Brands Senior Software Development Engineer to architect and lead the AI bidding platform for Amazon Sponsored Products and Brands. This role involves owning the technical strategy for real-time inference, GenAI agents, and experimentation infrastructure, focusing on sub-millisecond latency and autonomous learning at scale. Responsibilities include designing bidding engines, agentic intelligence layers using LLMs and RL, and experimentation systems, while also leading engineering efforts and mentoring teams. | AgentServe | 8 |
| Postdoctoral Scientist, Amazon Robotics Research and AI Development Postdoctoral Scientist role focused on AI-driven optimization for robotic fulfillment operations, involving automated optimization formulation, intelligent solver configuration, and fleet-level AI for dynamic task allocation. The role emphasizes research, publication in top-tier venues, and developing scalable solutions for robotic warehouses. | Agent | 8 |
| Applied Scientist II, Visual Search Science Applied Scientist II role focused on building generative AI and multimodal search systems for Amazon's visual search experience. The role involves designing, training, and optimizing text-to-image generation models, developing multimodal retrieval systems, building LLM-based classifiers for intent and safety, and architecting GPU-intensive inference pipelines. It operates at Amazon scale, serving hundreds of millions of customers. | AgentServe | 8 |
| Sr. AI Partner Solution Architect, ANZ Partner Team This role focuses on accelerating Generative AI, Agentic AI, and ML adoption by acting as a trusted technical advisor to AWS partners. The Senior AI Partner Solutions Architect will design and implement scalable AI/ML solutions using AWS services, guide partners on architectural patterns including agentic workflows and RAG, and deliver enablement programs. The ideal candidate has extensive hands-on experience with production AI systems and influencing technical and business decision-makers. | Agent | 8 |
| Sr. Applied Scientist, Amazon Robotics This role focuses on applying AI reasoning systems, specifically combining classical AI reasoning with Large Language Models (LLMs), to solve problems in robotics, automation, and fulfillment. The scientist will innovate on techniques for plan generation, correctness verification, learning reasoning strategies, and self-improving models, with an emphasis on publishing research and applying findings to business problems. | Agent | 8 |
| Software Dev Engineer II, EU INTech Partner Growth Experience, EU INTech Partner Growth Experience Software Development Engineer II role focused on building Agentic AI solutions for Selling Partners and Retail users, leveraging LLMs and specialized agents to improve user experience. The role involves working with Amazon's native/partnered LLMs and technologies like AgentCore, AgentMemory, Strands, and MCPs, with a focus on large-scale and high-performing systems. | Agent | 8 |
| SDE, AI Infrastructure, AFT AI Software Development Engineer to lead engineering efforts in developing infrastructure for agentic AI solutions in Amazon warehouses, including training and inference pipelines, and transforming research artifacts into scalable systems. | AgentServe | 8 |
| Senior Machine Learning Software Development Engineer, AI Ops Integration Senior Machine Learning Engineer role focused on designing and deploying production ML/LLM systems and agentic AI solutions for Amazon Operations & Supply Chain. The role involves end-to-end system design, data pipelines, model serving, orchestration of complex workflows, and ensuring safe and reliable operation of AI systems. It requires leadership in technical design, architecture, and engineering excellence across the ML lifecycle, with a focus on automating operational decisions at scale. | AgentServe | 8 |
| SDE-II, AI Core Infra - AI Analytics and Insights Software Development Engineer II on the AI Core Infra team at Amazon Advertising, focused on building and scaling the backend systems for a conversational AI assistant (SpektrBot) that uses generative AI and RAG to help users query advertising data. The role involves designing services, engineering RAG pipelines, integrating LLMs, building evaluation loops, and developing SQL generation capabilities. | AgentServe | 8 |
| Applied Scientist, Observability and Triage, Prime Video Applied Scientist role focused on building generative AI and large model systems for automated incident triage, root cause analysis, and resolution recommendation within Prime Video's observability and operational systems. The role involves prototyping, evaluating hypotheses, building evaluation frameworks, and collaborating with engineering teams to integrate ML models into production. | AgentEval Gate | 8 |
| Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect This role is for a Sr. Applied AI Solutions Architect focused on Amazon Connect's AI capabilities, specifically guiding customers in selecting foundation models, configuring AI prompts and agents, and architecting tool integrations for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and RAG. The role involves hands-on coding, building integrations, and configuring agents to move customers from proof-of-concept to pre-production. | Agent | 8 |
| Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect This role is for a Sr. Applied AI Solutions Architect focused on Amazon Connect's AI capabilities, specifically guiding customers in selecting foundation models, configuring AI prompts and agents, and architecting tool integrations for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and RAG. The role involves hands-on coding, building integrations, and configuring agents to move customers from proof-of-concept to pre-production. | Agent | 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 emphasizes end-to-end science from object detection to path planning and control, with a focus on real-world impact and scale. | AgentServe | 8 |
| Applied Scientist II, Perimeter Protection Applied Science This role focuses on designing, developing, and deploying AI/ML models for cybersecurity threats within AWS. It involves leveraging LLMs, generative AI, and agentic AI systems to build production-grade security solutions at scale, processing trillions of requests weekly. The role spans the entire ML lifecycle from data exploration to deployment and requires collaboration with engineers for integration into low-latency systems. | AgentServe | 8 |
| Software Development Engineer, Conversational AI Modeling and Learning Software Development Engineer/Machine Learning Engineer role focused on building and maintaining platforms for developing, evaluating, and deploying large language models for conversational agents. The role involves working with massive data, scaling ML models, optimizing latency and cost, and driving system architecture for high-performance, low-latency modeling solutions. | AgentServe | 8 |
| Applied Scientist, Agentic Automated Reasoning Applied Scientist role focused on building next-generation software verification tools by combining AI, cloud computing, and formal methods. The role involves understanding customer needs, identifying tools and methods, exploring generative AI for formalization and testing, and developing agentic systems for safety and security. | Agent | 8 |
| Applied Scientist, Agentic Automated Reasoning Group Pioneering next-generation neuro-symbolic tools by fusing AI breakthroughs with cloud scale and automated reasoning expertise. This role involves building scalable formal reasoning solutions integrated with GenAI and agentic AI for AWS customers, focusing on areas like hallucination detection and policy verification. The scientist will define and implement features, ensure software quality, and drive adoption of these advanced systems, with a potential to publish research. | AgentEval Gate | 8 |
| Senior Applied Scientist, Agentic Automated Reasoning Group Senior Applied Scientist role focused on pioneering neuro-symbolic tools by fusing AI breakthroughs with automated reasoning and cloud scale. The role involves defining and implementing automated reasoning features, applying software engineering best practices, and delivering high-quality scientific artifacts. Key responsibilities include designing and implementing production-grade neuro-symbolic systems, enhancing formal reasoning capabilities for GenAI and agentic applications (like hallucination detection and guardrails), and owning the end-to-end science lifecycle from research to production deployment. The role also involves mentoring junior scientists and advancing the state of the art through publications. | AgentEval Gate | 8 |
| Applied Scientist II, GenAI Evaluation Media (GEM) Applied Scientist II focused on GenAI Evaluation Media (GEM) for visual shopping experiences. The role involves research and development of agentic AI capabilities for visual understanding, content generation, personalization (virtual try-on), and automated quality assurance. It emphasizes multimodal understanding, real-time generation, and scalable personalization, integrating computer vision, NLP, and generative AI to create agentic shopping experiences. Success requires defining metrics, cross-functional collaboration, and staying at the forefront of AI advancements. The role requires rigorous research and practical engineering skills for production deployment. | AgentPost-train | 8 |
| Senior Security Engineer, Ads Security Senior Security Engineer focused on building AI-powered security automation solutions and agentic AI workflows for Amazon Ads. The role involves designing, developing, and evaluating AI systems for security use cases like anomaly detection and log analysis, with a focus on production deployment and continuous improvement. | AgentData | 8 |
| Principal Security Solutions Architect, AI-Driven Guidance, Well-Architected Solutions Innovation Principal Security Solutions Architect focused on defining and driving strategic vision for security-focused architectural guidance best practices across AI workloads on AWS. The role operates at the intersection of AI technologies, cloud architecture, and security engineering, ensuring AI workloads achieve Well-Architected outcomes with a deep focus on security. Responsibilities include setting technical direction, providing thought leadership on securing AI architectures (model security, data pipelines, prompt injection, inference endpoint hardening, secure agentic workflows), influencing service roadmaps, engaging with enterprise customers, driving innovation in content delivery, and hands-on technical validation. | Agent | 8 |
| Principal AI Compute SA, AGS Namer Tech This role is for a Principal AI Compute SA at Amazon Web Services (AWS), focusing on designing and architecting scalable, secure, and cost-effective AI/ML, Generative AI, and Agentic AI solutions for strategic enterprise accounts. The role involves acting as a subject matter expert and trusted advisor to customers, guiding them through their AI transformation journey, developing technical content, and collaborating with internal AWS teams to drive adoption of AWS AI services. The focus is on production-grade, responsible AI practices and enabling customers to leverage advanced AI capabilities on AWS. | Agent | 8 |
| Sr. Manager of Applied Science - Catalog Services, Product Knowledge GenAI Sr. Applied Science Manager to lead a team of scientists in building and scaling AI systems for deep product understanding, metadata organization, and generation within Amazon's e-commerce catalog. The role involves driving ML, NLP, and GenAI initiatives, creating agents, and delivering models into production. | AgentPost-train | 8 |
| Deep Learning Architect, AWS Gen AI Innovation Center This role focuses on designing, implementing, and scaling generative AI solutions for AWS customers, acting as a bridge between customer needs and AWS AI capabilities. It involves customer engagement, solution architecture, and providing guidance on best practices for responsible and cost-efficient AI deployment. | AgentPost-train | 8 |
| 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 Scientist, AWS Quick This role is for an Applied Scientist on the AWS Agentic AI team, focusing on building next-generation models for intelligent automation. The role involves defining and implementing automated reasoning features, applying software engineering best practices, and delivering high-quality scientific artifacts. The ideal candidate has experience in autonomous agents, API orchestration, planning, large multimodal models, reinforcement learning, and sequential decision making, with a strong publication record. | AgentPost-train | 8 |
| Sr. Applied Science , AWS Agentic AI This role focuses on building next-generation models for intelligent automation within AWS Agentic AI. The scientist will develop innovative solutions for complex problems, focusing on areas like autonomous agents, API orchestration, planning, large multimodal models (especially vision-language), reinforcement learning, and sequential decision making. The role involves partnering with technology and business teams, utilizing extensive data and computational resources, and collaborating with engineers. There's an expectation to publish findings at peer-reviewed conferences. | Agent | 8 |
| Applied Scientist, AWS Quick The AWS Agentic AI science team is looking for world-class researchers to build the next generation of intelligent automation models. The role involves developing innovative solutions for complex problems using autonomous agents, API orchestration, planning, large multimodal models (especially vision-language), reinforcement learning, and sequential decision making. Researchers are expected to publish their findings at peer-reviewed conferences and workshops, and apply software engineering best practices to ensure high-quality deliverables in an agile, startup-like environment. | Agent | 8 |
| Applied Science Manager, Personalization Manager for a team building Amazon's next-generation customer memory and personalization systems using LLMs, focusing on extracting, curating, and reasoning over customer knowledge for real-time personalization. The role involves end-to-end ML solution delivery, from problem formulation to production deployment at scale, and leading scientists in this domain. | 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 |
| Applied Scientist II, Amazon Quick This role focuses on developing innovative solutions for complex problems using autonomous agents, API orchestration, planning, large multimodal models (especially vision-language models), reinforcement learning, and sequential decision making. The candidate will define and implement new automated reasoning features, apply software engineering best practices, and publish findings at peer-reviewed conferences. The role is part of AWS and aims to solve real-world problems with access to significant data and computational resources. | Agent | 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 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 |
| 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 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 |
| 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 |
| 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 |
| 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 |