Currently tracking 1110 active AI roles, down 16% 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 |
|---|---|---|
| Sr Software Development Engineer, Neuron Collectives, Annapurna Labs Software Engineer role focused on optimizing collective operations for AWS Trainium, a purpose-built AI training chip. The role involves enhancing collective algorithms and topologies, identifying bottlenecks, and optimizing communication patterns to scale AI compute across the data center, working closely with hardware teams. | Data | 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, Sponsored Products and Brands - Advertiser Growth and Strategies This role focuses on designing and building agentic AI applications for Amazon advertisers. The primary responsibilities include developing agent architectures, creating tools and datasets, and building systems that can reason, plan, and act autonomously. The role involves working on fine-tuning, reinforcement learning, preference optimization, and evaluation frameworks to ensure safety and reliability. It also includes advancing the agent ecosystem through experimentation with tool orchestration, multi-step reasoning, and adaptive preference-driven behavior, ultimately aiming to create a personalized, context-aware agentic advertiser guidance system. | AgentPost-train | 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 |
| Software Development Engineer, Trust CX Innovations&AI Policy Software Development Engineer II role focused on building foundational systems and consumer-facing features for trustworthy and responsible AI experiences in consumer devices like Alexa and Echo. The role involves designing and implementing privacy-preserving AI architectures, federated learning, differential privacy, explainable AI interfaces, and AI safety guardrails, with a focus on balancing performance, privacy, and customer trust. | AgentServe | 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 |
| Senior Applied Scientist, Healthcare and Life Science Services Senior Applied Scientist role at AWS Applied AI Life Sciences focusing on designing, developing, and deploying novel Agentic systems and ML solutions for healthcare challenges. The role involves establishing ML best practices, collaborating with cross-functional teams, and mentoring junior scientists. | Agent | 8 |
| Applied Scientist, RL post-training, AWS This role focuses on Reinforcement Learning (RL) post-training of frontier LLMs to improve capabilities like instruction following, reasoning, and tool use, primarily for customer service applications within AWS. The role involves developing innovative solutions, publishing findings, and working with researchers and engineers. | Post-train | 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 Solutions Architect, AI-Driven Guidance, Well-Architected Solutions Innovation This role focuses on defining and driving the strategic vision for architectural guidance best practices for AI workloads on AWS. The Principal Solutions Architect will operate at the intersection of AI technologies and cloud architecture, ensuring AI workloads achieve Well-Architected outcomes. Key responsibilities include setting technical direction, providing thought leadership on Generative AI and Agentic AI (including foundation models, RAG, fine-tuning, prompt engineering, agentic workflows, multi-agent orchestration, and responsible AI), establishing quality standards and guardrails, influencing AWS service roadmaps, engaging with enterprise customers, driving innovation in content delivery, and providing hands-on technical validation through prototyping. | AgentServe | 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 |
| 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 |
| 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 |
| Software Development Engineer, Sponsored Products and Brands Software Development Engineer II to design and build AI-powered advertiser controls, including bidding systems, agentic architectures, and experimentation systems. The role involves developing AI engineering infrastructure, interfacing agentic architectures, and designing experimentation systems to optimize ad campaigns on Amazon. | AgentServe | 8 |
| Sr Applied Scientist III, Supply Chain Optimization Technologies - SCAIL This role focuses on designing, implementing, and evaluating innovative models and agents using Reinforcement Learning (RL) for supply chain optimization. It involves both advancing theoretical knowledge in ML/AI and applying these insights to real-world business problems, with an emphasis on research and publication. | Post-trainAgent | 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 |
| Applied Scientist, RBS Tech Applied Scientist role focused on designing and deploying GenAI, NLP, and Computer Vision solutions for customer experience and operations automation. Involves developing novel LLM, deep learning, and statistical techniques for various ML problems, with a focus on multi-modal LLM Agents and task automation. The role also includes defining research strategies, partnering with business/engineering teams, and potentially publishing research or filing patents. | AgentPost-train | 8 |
| Data Scientist II, RBS Tech The Data Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience and selling partner experience. The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques, and defining research strategies. Key areas include multi-modal understanding, task automation with LLM Agents, and improving product search results. The role also involves mentoring and potentially patent/publication contributions. | 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 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 |
| Head of Applied Science The Head of Applied Science at Audible will manage research teams, drive technical vision and strategy, and translate complex business requirements into production-ready ML solutions. This role involves leading the full development cycle from research to maintenance, evaluating new ML technologies, and collaborating across science, engineering, and product teams to deliver customer-facing AI products. | Ship | 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 |
| Senior Worldwide Specialist Solutions Architect - GenAI, Amazon Bedrock, Data & AI GTM Senior Solutions Architect for AWS GenAI services, focusing on helping enterprise customers design, deploy, and fine-tune GenAI applications using Amazon Bedrock and SageMaker. The role involves acting as a Subject Matter Expert, providing technical guidance, developing thought leadership content, and gathering customer feedback to influence product roadmaps. Requires deep technical experience with LLM architectures, fine-tuning, evaluation, and LLM-powered agents. | AgentPost-train | 8 |
| Member of Technical Staff - Simulation, Frontier AI Robotics The role focuses on developing 3D physics-based and photorealistic simulations for training large-scale machine learning models in robotics. This involves creating simulations for reinforcement learning, generating synthetic data, implementing robotics features, and building real-to-sim workflows to minimize sim-to-real gaps. The goal is to support the training of foundation models for robotics. | DataPost-train | 8 |
| Applied Scientist II, Alexa Edge AI Applied Scientist II on the Alexa Edge AI team, focusing on deep learning and speech processing to develop novel ML algorithms for speech and audio. This role involves applied research, model design, training, and optimization for consumer products. | Post-train | 8 |
| Senior Applied Scientist Senior Applied Scientist to lead the development of next-generation object tracking systems for autonomous robots, fusing classical estimation theory with modern learning-based approaches. The role involves architecting robust, real-time tracking pipelines, developing sensor fusion, pioneering learning-based tracking methods, and establishing evaluation frameworks for safe and intelligent robot behavior. | AgentData | 8 |
| Sr GenAI Infra Specialist SA, AWS WWSO Startup Senior GenAI Infrastructure Specialist SA for AWS WWSO Startup team, focusing on advising startup customers on AI infrastructure for model training and inference optimization. This role involves deep technical guidance on hardware, orchestration, frameworks, and optimization techniques for large-scale AI workloads on AWS. | ServePost-train | 8 |
| Applied Scientist III, Whole Body Control This Applied Scientist III role focuses on developing advanced robotics systems by applying deep learning and large language models to whole body control for balance, locomotion, and dexterous manipulation. The role involves implementing real-time controllers and collaborating with multi-disciplinary teams to shape the future of automation and human-robot collaboration. | ShipAgent | 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 |
| 2027 Applied Science Intern (Computer Vision), Amazon International Machine Learning Internship role focused on Computer Vision and Machine Learning research, developing novel solutions and prototypes with the potential for production impact. Collaboration with researchers and publication in top-tier conferences are key aspects. | Post-trainServe | 8 |
| AI Solution Architect AWS is seeking an AI Specialist Solution Architect to guide customers in adopting GenAI/ML and Agentic technologies. This role involves building technical relationships, crafting scalable architectures, and providing expert advice on security, cost, performance, and operational efficiency for AI/ML projects. The architect will also contribute to AWS's roadmap by sharing customer needs and creating technical content like whitepapers and reference architectures. | AgentServe | 8 |
| Senior Machine Learning Software Development Engineer, AI Ops Integration Senior Machine Learning Software Development Engineer focused on integrating AI Operations within Amazon's Supply Chain. The role involves designing and deploying production ML/LLM systems and agentic AI solutions, orchestrating complex workflows, and defining technical strategy for internal tooling. Responsibilities include end-to-end system design, integration architecture, driving engineering excellence across the ML lifecycle, and implementing safety measures like guardrails and evaluation frameworks. The role also involves mentoring junior engineers and partnering with stakeholders to translate business problems into technical solutions. | AgentServe | 8 |
| Machine Learning Software Development Engineer, AI Ops Integration Machine Learning Software Development Engineer to build and deploy ML/LLM-powered features, implement AI agent components for automating workflows, develop internal front-end applications, build integrations for multi-system orchestration, and contribute to the ML lifecycle including guardrails and evaluation frameworks. The role focuses on solving operational problems at scale within Amazon Operations & Supply Chain. | AgentServe | 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 , Prime Video Ads Senior Applied Scientist role focused on building and deploying ML models for personalizing advertising experiences on Prime Video. The role involves research and development across the ML lifecycle, from exploratory research to production deployment, with a focus on understanding heterogeneous customer responses, inferring preferences from indirect signals, and optimizing for competing objectives like revenue and customer engagement at massive scale. | ShipAgent | 8 |
| Postdoctoral Scientist, Amazon Robotics R&D Postdoctoral Scientist role in Amazon Robotics R&D focusing on computer vision and robotic manipulation for automating picking operations in fulfillment centers. The role involves developing ML solutions for robots to identify and interact with items in cluttered 3D scenes in real-time, with a focus on pushing research boundaries and deploying innovations to real warehouses. | ShipData | 8 |
| Senior Applied Scientist, Fauna This role focuses on developing evaluation frameworks and data collection protocols for robotic capabilities, operating at the intersection of robotics, machine learning, and human-in-the-loop systems. The scientist will design how to measure, stress-test, and improve robot behavior, build infrastructure connecting teleoperation, evaluation, and learning, and lead technical projects. | Eval GateAgent | 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 |
| Applied Scientist I Applied Scientist role focused on developing novel algorithms and modeling techniques for speech and language technologies (ASR, NLU, TTS, Dialog Management) impacting millions of customers. Requires ML background and programming experience, with preferred qualifications in AI/ML technologies, large-scale systems, and publications in top-tier conferences. | Post-train | 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 |
| Machine Learning Engineer, CreativeX Machine Learning Engineer to join the CreativeX RAPID team, focusing on Dynamic Creative Optimization (DCO). The role involves leveraging generative AI technologies like latent diffusion models, LLMs, RL, and computer vision to tailor ad experiences in real-time with low latency. Responsibilities include investigating new technologies, prototyping, evaluating feasibility, building data pipelines, and developing ML model deployment platforms. | ServePost-train | 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 |
