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, Alexa for Shopping Science UK Applied Scientist II role focused on developing and optimizing LLM/SLM powered conversational experiences for Alexa Shopping. This involves designing and implementing LLM agents, instruction design, contextual grounding, using MCP tools, agent/multi-agent systems, context engineering, model fine-tuning, and evaluation frameworks. The role also involves applying ML/DL techniques for last-mile improvements in ranking, relevance, personalization, and multimodal understanding, and designing agentic architectures with considerations for quality, latency, and reliability at scale. It requires hands-on analysis of multimodal interaction datasets, using statistical methods for evaluation and optimization, and collaborating with product and engineering teams. | AgentPost-train | 9 |
| Applied Scientist, Alexa International Tech |
| Post-trainServe |
| 9 |
| Applied Sciences Manager , Ads Brand Safety and Suitability Manager for an Applied Sciences team focused on building AI-powered Brand Safety and Content Classification systems for Amazon Ads. The role involves leading the development of next-generation systems that make millisecond-level decisions across billions of content signals, adapting to emerging risks from generative AI. Key challenges include detecting AI-generated content, understanding contextual brand risk, designing adaptive models, and leveraging LLMs for real-time semantic understanding at internet scale. | AgentServe | 9 |
| Applied Scientist - LLM, Alexa Applied Scientist role focused on training and deploying LLMs for conversational AI systems like Alexa. The role involves end-to-end ownership from research and algorithm development to production deployment and inference infrastructure. | Post-trainServe | 8 |
| Data Scientist II, RufusX Science UK Data Scientist II role focused on developing and optimizing AI-driven conversational and multimodal shopping experiences using NLP, ML, and large language models. The role involves analyzing large datasets, building predictive models, designing experiments, and collaborating with scientists and engineers to launch features and systems. It touches on inference infrastructure and agentic systems for shopping tasks. | AgentServe | 8 |
| Data Scientist II, Alexa for Shopping Science UK Data Scientist II role focused on building and optimizing AI-driven conversational shopping experiences for Alexa. The role involves developing multimodal systems using NLP, ML, and LLMs, with a focus on agentic capabilities, information retrieval, recommender systems, and knowledge graphs. Responsibilities include data analysis, modeling, experimentation, A/B testing, metric development, and collaboration with scientists and engineers to launch features and systems. The role also touches on inference and serving infrastructure. | AgentServe | 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, 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 |
| Applied Scientist, Edge AI and Science Applied Scientist role focused on compressing generative AI models (LLMs, VLMs, speech, audio, omni) for edge and cloud deployment. The role involves applying and extending state-of-the-art compression techniques (knowledge distillation, pruning, quantization), designing healing recipes (fine-tuning) to recover accuracy, building reference implementations for partner teams, and defining benchmarks for evaluating trade-offs (accuracy, latency, memory, cost). The goal is to make training-to-deployment seamless. | ServePost-train | 8 |
| Applied Science Manager, Alexa International Manager for a team of Applied Scientists focused on building and enhancing multilingual speech models (understanding and generation) for Alexa. The role involves leading the team, setting technical direction, driving scientific strategy, and ensuring end-to-end delivery of speech quality improvements from research to production. Key areas include speech-to-speech models, text-to-speech synthesis, multilingual systems, and leveraging large-scale data and computing resources. | Post-trainServe | 8 |
| Sr. Applied Scientist, Alexa International Senior Applied Scientist role focused on developing and advancing multilingual speech models (understanding and generation), text-to-speech synthesis, and speech-to-speech models for Alexa International. The role involves driving scientific strategy, leveraging large-scale computing resources, and optimizing model performance for production deployment in low-resource language settings. | Post-trainServe | 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 |
| 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 |
| Senior Applied Scientist (Computer Vision), Camera and Sensors Senior Applied Scientist focused on computer vision and multimodal perception models for Amazon devices, involving algorithm development, experimentation, and implementation with large-scale data and computing resources. | Ship | 8 |
| Applied Scientist II, Strategic Account Services (SAS) Applied Scientist II role focused on developing and deploying sophisticated AI solutions for Amazon's Strategic Account Services (SAS) organization, leveraging deep learning, LLMs, and advanced ML techniques to improve seller operations and internal consultancy. The role involves end-to-end development from research to production, including architecting recommendation and optimization systems, pioneering applications of foundation models, and conducting rigorous A/B experiments. | ShipServe | 8 |
| Forward Deployed AI Integrator , Field Engineering This role focuses on integrating AI-assisted workflows within regional Field Engineering teams at AWS. The Forward Deployed AI Integrator will identify opportunities, drive adoption of AI tools, and convert experiments into repeatable standards, aiming to deliver measurable productivity outcomes. It's a hands-on execution role measured by transformed workflows and engineering hours saved. | Agent | 7 |
| Applied Scientist, Silicon and Systems Group Edge AI Research Scientist role focused on developing novel evaluation methods for multimodal language models and agents for consumer devices. This involves creating and validating automated evaluation techniques, analyzing datasets to understand model gaps, and collaborating with training teams. The role emphasizes hardware-software integration for efficient model training and deployment on edge devices. | Eval GatePost-train | 7 |
| Senior Customer Solutions Manager, Aerospace and Satellite This role is for a Senior Customer Solutions Manager at Amazon Web Services (AWS) within the Aerospace & Satellite team. The primary focus is to act as a trusted advisor to senior stakeholders in aerospace and satellite organizations, guiding them on cloud technology and AI adoption to accelerate their missions. The role involves leading complex customer engagements, driving strategic execution of cloud adoption roadmaps, and accelerating value through modernization, generative AI, and agentic AI. It also includes enabling customers for responsible AI adoption and navigating ambiguity in dynamic situations. The role emphasizes understanding customer goals and driving end-to-end execution across AWS teams to deliver business outcomes. | Agent | 7 |
| Applied Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services Design and implement machine learning models for recommendation systems in talent acquisition at Amazon, focusing on fairness and explainability. The role involves full software development lifecycle, collaboration with cross-functional teams, and staying current with scientific literature to improve hiring processes. | ShipAgent | 7 |
| Sr Manager, International Shopping AI Product, Alexa for Shopping Senior Manager, Product Management, AI Shopping, International to lead a team of Product Managers and Editors who help train AI models to deliver helpful, delightful conversational experiences for customers. This role advocates for and supports product parity efforts across international marketplaces by evaluating features pre-release and producing locally relevant insights to guide refinements. They guide efforts to automate evaluations, tune prompts, and localize experiences, enabling our AI Shopping initiatives to scale internationally. The team delivers delightful, locally relevant conversational experiences through LLM data curation and editing, evaluation, and prompt engineering. | Post-trainData | 7 |
| Software Development Manager, Amazon Rufus This role is for a Software Development Manager at Amazon, focused on building a new generative AI-powered shopping and search experience. The goal is to create intuitive, conversational interfaces that synthesize complex information and provide trustworthy recommendations, aiming to make AI shopping a major business pillar for Amazon. The role involves leading engineers, scientists, and product leaders to innovate and deliver AI products at scale. | Ship | 7 |
| Applied Scientist, Advertising The role focuses on designing and implementing deep learning models for ad matching in Amazon's programmatic advertising products. It involves optimizing ad selection based on customer behavior and contextual information to predict conversion propensity, ultimately driving better campaign outcomes for multi-billion dollar businesses. The work impacts high-throughput production systems and requires collaboration with engineers and product teams. | Ship | 7 |
| Principal GenAI GTM Specialist, WWSO This Principal GenAI GTM Specialist role focuses on driving enterprise adoption of Generative AI across EMEA, specifically leveraging Amazon Bedrock and agentic architectures. The role involves developing and executing go-to-market strategies, translating technical capabilities into business outcomes, and acting as a thought leader and trusted advisor to senior customer stakeholders. It requires a blend of deep technical proficiency in GenAI and commercial acumen to land AI transformation programs. | Agent | 7 |
| Applied Scientist, Agentic Automated Reasoning The role focuses on building next-generation software verification tools by combining AI, cloud computing, and domain expertise. It involves applying generative AI techniques to formalize requirements, generate tests, and assist in program proofs for code analysis problems. The team specifically works on AI-based agents and ensuring they operate within safety boundaries. | Agent | 7 |
| Software Development Engineer, Rufus Software Development Engineer to build and improve a generative AI-powered shopping assistant for millions of Amazon customers. The role involves full vertical end-to-end ownership of features, working with product and design teams, and contributing to architecture and design. | Ship | 7 |
| Software Development Engineer, Advertising Software Engineer role focused on optimizing ad matching for Amazon's programmatic advertisement products. This involves working with machine learning models at high scale and low latency, applying MLOps and Software Engineering best practices to process large datasets, and integrating experimental results into production systems. The role emphasizes designing, testing, and delivering breakthroughs for Amazon's business, impacting multi-billion dollar businesses. | Ship | 7 |
| Senior Specialist Solutions Architect, Agentic Engineering / Kiro Senior Specialist Solutions Architect focused on driving adoption of AWS Agentic Engineering offerings, including Kiro, Claude Code on Bedrock, and AWS Frontier Agents, within the startup ecosystem. The role involves technical thought leadership, go-to-market program execution, and collaboration with engineering teams to influence product roadmaps. Requires experience in customer-facing roles, AI/ML or generative AI, and modern SDLC automation. | Agent | 7 |
| Data Scientist II, Intelligent Talent Acquisition This role focuses on leveraging Gen AI and multi-agent systems to revolutionize hiring processes at Amazon. The Data Scientist will develop and deploy ML models for anomaly detection, root cause analysis, and candidate quality optimization, aiming to improve efficiency and reduce defect detection time. The role involves working with AWS infrastructure and designing experiments to evaluate system stability and attract top talent. | AgentServe | 7 |
| Senior Applied Scientist, Insights, Prime Video Senior Applied Scientist role focused on developing machine learning algorithms for high-scale recommendations problems within Prime Video. The role involves designing, prototyping, and integrating ML models into production systems, with a focus on generative AI and large models to reduce operational load and deliver personalized recommendations. | Ship | 7 |
| Sr. Manager, Software Dev, Next-Gen Security Automation The role is for a Senior Manager of Software Development focused on building next-generation Agentic security systems at Amazon. The position involves leading teams to create AI-powered security products from the ground up, working at the intersection of AI and security at a large scale. The manager will collaborate with security, engineering, and science leaders, and shape products that transform business security practices. | Agent | 7 |
| Applied Scientist, Amazon Transportation Applied Scientist role focused on building machine learning and optimization models for Amazon's large-scale transportation planning systems, including dynamic pricing and network planning. The role involves designing, building, and implementing scalable products and algorithms within production systems, with a focus on external freight and marketplace operations. | Ship | 7 |
| Applied Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services The role involves designing and implementing machine learning models for recommendation systems to improve Amazon's talent acquisition processes. It focuses on building ML products that match job seekers with opportunities and recruiters with talent, operating at a global scale. The work involves representation learning, reinforcement learning, and probabilistic modeling, with an emphasis on fairness and explainability. | ShipAgent | 7 |
| Sr AI Editorial Lead (Portuguese), AI Shopping, International This role focuses on curating and evaluating content to train and optimize AI models for conversational shopping experiences in new marketplaces and languages. It involves defining guidelines, ensuring response quality, analyzing errors, and creating frameworks for prompt tuning and management. The role also guides the development of automation and internal tools for editorial curation and evaluation, collaborating with product, science, and engineering teams. | Post-trainData | 7 |
| Software Development Engineer, Ring Cloud Computer Vision Software Development Engineer role focused on building and scaling AI-powered computer vision cloud services for Ring's consumer electronics products, serving tens of millions of users globally. The role involves full software development lifecycle, from design and development to deployment and operations, with a focus on high-availability, resilience, and scalability. | Ship | 7 |
| Process Analyst, EU Central Operations Analytics This role focuses on designing and implementing AI-powered automation solutions and machine learning models to enhance last-mile delivery operations within Amazon Logistics. The Process Analyst will work at the intersection of operations, analytics, and automation, developing and deploying intelligent systems for forecasting, capacity management, and decision support. The role involves translating operational challenges into automated solutions using SQL, Python/R, and AI/ML capabilities, creating intelligent dashboards, predictive models, and automated reporting systems. It requires partnering with Data Science and Engineering teams to deploy AI/ML solutions into production and evaluating emerging AI technologies. The position emphasizes leading AI/automation projects from conception to scaling, balancing business requirements with technical feasibility, and influencing cross-functional teams. | Agent | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and implementing state-of-the-art solutions for complex problems, potentially leading to production deployment and publication. | Ship | 7 |
