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, 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 |
| Senior Applied Scientist, AWS Agentic Automated Reasoning Group Senior Applied Scientist role focused on building scalable neuro-symbolic systems that fuse formal reasoning with GenAI and agentic AI for AWS customers, aiming to deliver reliable, verifiable outcomes and enhance features like hallucination detection and guardrails. The role involves end-to-end ownership from research to production, collaboration, and mentoring. |
| AgentEval Gate |
| 8 |
| Software Development Engineer, Sponsored Products and Brands Software Development Engineer role focused on building an Agent platform using Generative AI and ML technologies for Amazon Ads. The role involves designing and developing scalable systems for personalized ad experiences, optimizing for cost and latency, and pioneering new approaches to conversational AI. The team owns the SPB Agent, which powers reasoning behind agentic experiences in Ads Console, Sales, and Seller Central. | Agent | 8 |
| Applied Scientist II, Sponsored Products and Brands-Agent The role focuses on building a personalized and context-aware agentic advertiser guidance system using LLMs and sophisticated tooling for Amazon Ads. It involves integrating LLMs with tools, operating across various advertiser-facing platforms, and delivering solutions through advanced agent architectures and model customization. | Agent | 8 |
| Software Development Engineer, ML Systems, Annapurna Labs Software Development Engineer role focused on building AI agents and tools to simplify and accelerate customer adoption of Amazon's AWS Neuron ML software stack, which supports Trainium and Inferentia ML chips. The role involves applying Generative AI to AI itself, identifying obstacles, and developing solutions to improve the porting and optimization of ML workloads on AWS ML silicon. | Agent | 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 |
| Data Scientist II, Enterprise Security Products Data Scientist II role focused on building AI-first security products, including designing, training, and shipping ML models for agentic systems, anomaly detection, and threat classification. The role involves owning the full ML lifecycle, using AI tools to accelerate development, and powering multi-agent security systems with RAG pipelines and evaluation frameworks. It emphasizes rapid prototyping, customer validation, and collaboration across disciplines. | AgentPost-train | 8 |
| AI Solution Architect AI Specialist Solutions Architect for AWS, focusing on helping enterprise customers adopt and scale GenAI, ML, and Agentic technologies. The role involves designing technical architectures, advising on best practices, and acting as a trusted advisor to customers, with a strong emphasis on production deployment and operational efficiency. | AgentServe | 8 |
| Senior Software Engineer, Leo Satellite Build Intelligence Senior Software Engineer role focused on building AI systems for satellite manufacturing intelligence. The role involves architecting and implementing a platform that connects design, production, test, and quality data, utilizing AI-native workflows with retrieval systems, foundation models, agentic tool use, and human review. Key responsibilities include designing AI-native workflows, creating evaluation mechanisms for AI quality, and building production software. The role emphasizes building agentic systems (L4) with a strong focus on evaluation and quality gates (L5). | AgentEval Gate | 8 |
| Applied Scientist II, Payment Risk Machine Learning Applied Scientist II role focused on building and deploying machine learning models and agentic AI systems for payment risk management and fraud detection at Amazon. The role involves end-to-end development, from data analysis and model design to production deployment and monitoring, utilizing techniques like deep learning, LLMs, graph neural networks, and multi-agent systems. | AgentServe | 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 |
| SDE II, Same Day Delivery Software Development Engineer II role on the Same Day Delivery Experience team, focusing on building and scaling AI-powered tools using LLMs, RAG, NLP, prompt engineering, and agentic AI workflows to enhance customer experience and protection. Responsibilities include designing and building AI tools, developing retrieval pipelines, prototyping agentic AI capabilities, and working on scalable AI/ML systems. | Agent | 8 |
| Customer Solutions Manager, Prototyping & Customer Engineering This role focuses on leading 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 goal is to help customers experiment with innovative approaches and validate the technical feasibility of AI solutions, shaping how organizations adopt AI. | Agent | 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 |
| 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 |
| 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 |
| 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 |
| 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, 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 |
| Senior Applied AI Solutions Architect, Federal Financial Senior Applied AI Solutions Architect for Federal Financial Regulatory customers, focusing on designing and enabling AI/ML solutions for fraud detection, market surveillance, regulatory reporting, and consumer protection. The role involves technical guidance, developing reference architectures, and enabling customer adoption of AI/ML on AWS, with a strong emphasis on agentic systems and RAG. | Agent | 8 |
| Senior Applied Scientist, FinTelligence Senior Applied Scientist role at Amazon's FinTech organization, focusing on building and scaling generative AI applications and autonomous agents for financial operations. The role involves developing systems that process financial transactions, extract intelligence from documents, and power agents that learn from customer interactions. Key responsibilities include ensuring AI systems are trusted for compliance, designing agents that improve with user feedback, optimizing inference at scale using tiered models and LLMs, and developing robust evaluation frameworks. The position emphasizes shipping production-ready models, working across the full stack, and solving complex real-world financial problems. | AgentServe | 8 |
| Applied Science Manager, Sponsored Products and Brands Manager for the Amazon Sponsored Agent (ASA) team, focusing on building and scaling a new agentic service for conversational and agentic ads. The role involves leading a team to develop a multi-agent system architecture for contextual ad serving, conversation understanding, and commercial insights generation, with a focus on AI-native ad formats. | AgentServe | 8 |
| Deep Learning Architect, AWS Gen AI Innovation Center This role involves designing, implementing, and fine-tuning state-of-the-art Generative AI solutions for AWS customers, focusing on real-world problem-solving and production deployment. The architect will collaborate with customers and internal teams to understand business needs, develop proof-of-concepts, and guide adoption patterns. | AgentPost-train | 8 |
| 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 |
| 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 Manager, Seller Assistant, SPX Seeking a Software Development Manager to lead the development of a next-generation, GenAI-first, multi-agent system for Amazon Seller Assistant. This role involves owning end-to-end development of agentic capabilities at Amazon's scale, partnering with scientists and engineers to launch production-grade systems used by millions of sellers. | AgentShip | 8 |
| Machine Learning Engineer, Data & Machine Learning (DML) Machine Learning Engineer on AWS Professional Services team, focusing on designing, implementing, and scaling Generative AI solutions for customers. Requires TS/SCI clearance. | AgentPost-train | 8 |
| Machine Learning Engineer, Data & Machine Learning (DML) Machine Learning Engineer role focused on designing, implementing, and scaling AI/ML solutions for AWS customers. This involves selecting, fine-tuning, and deploying models, identifying use cases, and providing technical guidance on responsible AI adoption. The role requires experience with ML/statistical modeling, software engineering best practices, and a Top Secret security clearance. | AgentPost-train | 8 |
| Senior Applied Scientist, Entertainment Devices & Grocery Experiences (EDGE) Ads Senior Applied Scientist role focused on improving advertising performance and delivering innovative advertising experiences for Amazon devices and grocery. The role involves building and deploying machine learning models, with a specific emphasis on agentic AI for ads targeting, including autonomous agents, multi-agent orchestration, large multimodal models, reinforcement learning, and sequential decision making. The position requires experience in developing scalable data pipelines, optimizing conversion KPIs, and staying updated with the latest advancements in ML, NLP, and multimodal learning. | Agent | 8 |
| Applied Scientist, Traffic Quality Applied Scientist II role focused on detecting sophisticated invalid traffic (IVT) in advertising using deep learning, self-supervised techniques, representation learning, and advanced clustering. The role involves defining research problems, inventing ML approaches, designing and deploying production-quality ML components, and working with massive datasets. It also requires producing research reports and contributing to the scientific community through publications. | Agent | 8 |
| Sr. Software Development Manager, MHLS Tech This role manages multiple engineering teams responsible for building and scaling AI-powered conversational systems, knowledge management platforms, and intelligent routing solutions for Amazon's global employee support platform. The focus is on defining and executing the AI/ML strategy for production generative AI systems, including LLMs and agentic frameworks, while ensuring scalability, reliability, and responsible AI practices. | AgentServe | 8 |
| Applied Scientist , Amazon Customer Service Applied Scientist II role focused on building AI-based automated customer service solutions using RAG, agentic AI, and post-training of LLMs. Responsibilities include designing and deploying RAG pipelines, conducting LLM post-training, curating datasets, implementing evaluation frameworks, developing AI agents, and collaborating with cross-functional teams. The role involves research and development with minimal guidance, aiming to translate research into production systems and contribute to the scientific community. | AgentPost-train | 8 |
| Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect This role focuses on accelerating customer adoption of Amazon Connect's AI capabilities by acting as an Applied AI Solutions Architect. The architect will guide customers in selecting foundation models, designing and optimizing AI prompts, and architecting tool integrations for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and helping customers move from proof-of-concept to pre-production for Amazon Connect + Unlimited AI deployments. The role involves hands-on coding, building integrations, configuring agents, and collaborating with customer engineering teams. | Agent | 8 |
| Senior Machine Learning Engineer, AWS Identity Analytics Platform Senior Machine Learning Engineer at AWS Identity Analytics Platform, focusing on building an AI-driven analytics platform that processes petabyte-scale data to generate insights for security and operational problems. The role involves designing, developing, and deploying ML solutions, including anomaly detection, time-series forecasting, classification, optimization models, and LLM-powered agents for conversational data querying. It also includes feature engineering, production deployment, and collaboration with leadership and service teams. | AgentData | 8 |
| Senior Economist, SEI Science Team Senior Economist to define and build GenAI-first, multi-agent systems for Amazon Seller Assistant, owning capabilities end-to-end from insight to shipped product. Focus on agentic experiences, translating research into production, and designing evaluation frameworks. | Agent | 8 |
| Senior Applied AI Solutions Architect — Amazon Connect Senior Applied AI Solutions Architect for Amazon Connect, focused on accelerating customer adoption of AI capabilities. The role involves guiding customers in model selection, prompt configuration, and tool integration for AI agents, with a strong emphasis on customer data readiness and enabling multi-agent orchestration. This is a hands-on role requiring coding, integration building, and pair-programming with customer teams to move from proof-of-concept to production. | Agent | 8 |
| Sr.Product Manager - Tech Senior Product Manager, Technical role focused on defining product strategy and roadmap for Generative AI applications in compliance and safety. This involves partnering with Applied Scientists and Engineering teams to build and scale LLM-based systems, design human-in-the-loop systems, and establish AI governance frameworks for responsible AI deployment in high-stakes compliance scenarios. The role requires technical depth in AI/ML, product management expertise, and collaboration across multiple teams. | AgentEval Gate | 8 |