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 |
|---|---|---|
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. The role emphasizes using AWS AI/ML services and involves working with customers to achieve their business outcomes. | ServePost-train | 7 |
| Post-Silicon Systems Validation Engineer, Annapurna Labs This role focuses on validating next-generation machine learning accelerators for AWS, covering the entire vertical stack from silicon to system. The engineer will work on hardware and software validation, ensuring performance, accuracy, and reliability of ML accelerators used in AWS data centers. Responsibilities include developing validation strategies, executing test plans, debugging hardware and software issues, and collaborating with cross-functional teams. |
| Serve |
| 7 |
| Sr. System Development Engineer, High-Performance Accelerator Servers for AI/ML This role is for a Senior System Development Engineer focused on high-performance accelerator servers for AI/ML at AWS. The engineer will be responsible for designing, delivering, and operating next-generation infrastructure for AI training and inference, focusing on performance, efficiency, and scalability. The role involves deep technical understanding of the full stack from hardware to software, systems debugging, and leading complex projects. | Serve | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. The role requires experience in hosting and deploying GenAI/ML solutions, including pre-processing, training, fine-tuning, and inference. | ServePost-train | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing AWS GenAI/ML solutions for customers, providing technical guidance, and acting as a trusted advisor. It involves working with customers to understand their needs and proposing effective strategies for model training, building, and deployment, with a strong emphasis on using AWS AI/ML services. | ServePost-train | 7 |
| Post-Silicon Systems Validation Engineer, Annapurna Labs This role focuses on validating next-generation machine learning accelerators for AWS cloud infrastructure, covering the entire vertical stack from silicon to system. The engineer will be responsible for developing validation strategies, executing test plans, conducting hands-on bring-up and debug, and validating ML accelerator performance using real-world workloads. The role requires collaboration with various engineering teams and a strong understanding of computer architecture and ML fundamentals. | Serve | 7 |
| Senior Video Compression Development Engineer, AWS Elemental, Elemental Video Engine Senior Software Development Engineer focused on video compression, responsible for writing code to process customer video and metadata. The role involves working on video technologies like VVC, AV1, HEVC, AVC, high dynamic range video, and enhancement filters. A key aspect is utilizing ML and Generative AI to solve new problems, improve video quality, enable new use cases, and enhance compute performance of video processing. The engineer will also design and implement improved video filters and contribute to home-grown video encoders. | Serve | 7 |
| Professional Services III AMZ13646.13 This role focuses on building and deploying scalable ML/AI solutions within AWS, leveraging Big Data, AppDev, or DevOps experience. It involves close collaboration with Data Scientists and Data Engineers to deliver end-to-end solutions for customers, utilizing ML frameworks, algorithms, and cloud technologies. | ServeData | 7 |
| Sr Solutions Architect, Annapurna ML This role is for a Sr. Solutions Architect focused on AWS Machine Learning accelerators (Inferentia and Trainium). The individual will work with customers to develop and deploy Deep Learning models on these accelerators, acting as a trusted advisor and thought leader. Responsibilities include designing architectures, owning PoCs, driving adoption through technical engagements, and sharing best practices. The role bridges customer needs with engineering roadmaps and involves creating technical content for various audiences. | Serve | 7 |
| Delivery Consultant - AI/ML, Professional Services - AWS Industries This role focuses on designing, implementing, and deploying GenAI and ML applications for customers on AWS. It involves providing technical guidance, gathering requirements, and supporting model training, building, and deployment strategies. The role requires experience with AWS AI/ML services and hosting/deploying ML solutions, with a preference for deep learning experience. | ServePost-train | 7 |
| Delivery Consultant - AI/ML, Professional Services - AWS Industries This role focuses on designing, implementing, and managing AI/ML solutions on AWS for customers, with a strong emphasis on deploying these solutions. The consultant provides technical guidance, collaborates on model training and deployment strategies, and acts as a trusted advisor on AI/ML trends. The role requires experience in software development, cloud architecture, and specifically hosting/deploying GenAI/ML solutions. | ServePost-train | 7 |
| Delivery Consultant - AI/ML & Data Science, Professional Services - AWS Industries This role focuses on designing, implementing, and managing AWS solutions for customers, with a specific emphasis on GenAI and ML applications. The consultant will provide technical guidance, gather requirements, and propose strategies for model training, building, and deployment, acting as a trusted advisor on industry trends and emerging technologies. The role involves hands-on experience with deploying GenAI/ML solutions on AWS. | ServePost-train | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing GenAI and ML applications and models on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. Experience with hosting and deploying GenAI/ML solutions is required. | ServePost-train | 7 |
| Delivery Consultant - AI/ML, Professional Services - AWS Industries This role focuses on designing, implementing, and deploying GenAI and ML applications for customers on AWS. It involves providing technical guidance, gathering requirements, and supporting model training, building, and deployment strategies. The role requires experience with AWS AI/ML services and hosting/deploying ML solutions, with a preference for deep learning experience. | ServePost-train | 7 |
| Senior Delivery Consultant - AI/ML, AWS Professional Services Senior Delivery Consultant for AWS Professional Services focusing on designing, implementing, and managing AI/ML and Generative AI solutions for enterprise customers. This role involves leading project teams, hands-on development, MLOps, and acting as a trusted advisor on cloud AI architectures. | ServeAgent | 7 |
| Software Development Engineer, Alexa Audio Software Development Engineer role focused on integrating Generative AI and LLM capabilities into Alexa's audio experiences. The role involves designing and implementing software, creating infrastructure for LLMs in audio, developing tools to evaluate and improve model accuracy, reducing latency, and influencing operational excellence for audio services. It also includes mentoring junior engineers and contributing to hiring efforts. | ServePost-train | 7 |
| ML Accelerator Performance Validation Engineer, Post Silicon Validation This role focuses on validating the performance of custom ML training chips for AWS, ensuring they meet latency, throughput, and efficiency targets at cloud scale. The engineer will design and execute performance benchmarks, profile ML workloads on silicon, identify bottlenecks, and build automated dashboards to track performance and readiness for production deployment. | Serve | 7 |
| Software Development Engineer, Item Identity Services (IIS) Software Development Engineer to help architect, build, and ship an AI-native matching platform that replaces legacy rule-based and classical ML matching algorithms with LLM-powered AI systems. The role involves serving LLM-based inference over petabyte-scale product data with sub-millisecond latency requirements, handling millions of requests per second, and solving novel computer science problems at the intersection of LLMs, retrieval, distributed systems, and large-scale data processing. | ServeAgent | 7 |
| Applied Scientist, AWS Neuron Science team Applied Scientist role focused on enhancing the AWS Neuron software stack for Trainium and Inferentia accelerators. The role involves working with customers to identify adoption barriers, collaborating with engineering teams on solutions, and engaging with research communities to advance ML systems. Key areas include AI for Systems (kernel/code generation, optimization), Machine Learning Compiler, System Robustness, and Efficient Kernel Development. | ServeData | 7 |
| Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs Senior Software Engineer role focused on building and optimizing the AWS Neuron compiler for AWS Inferentia and Trainium chips. The role involves transforming ML models (PyTorch, TensorFlow, JAX) into optimized implementations for deep learning workloads, with a focus on large language models and vision transformers. Responsibilities include compiler optimization, working with chip architects, and contributing to open-source communities. | Serve | 7 |
| Machine Learning Engineer II, Sponsored Products Search Sourcing, Amazon Advertising Machine Learning Engineer II at Amazon Advertising focused on building and optimizing ML systems for Sponsored Products and Brands search, handling billions of requests with low latency. The role involves developing scalable offline pipelines and online serving components, working with deep learning, NLP, and LLM training, and mentoring junior engineers. | ServePost-train | 7 |
| Sr. ASIC Engineer III, Annapurna Labs The Sr. ASIC Engineer III role at Amazon's Annapurna Labs focuses on the design and optimization of custom silicon (ASICs) and software that accelerate machine learning inference in AWS data centers, specifically for hardware like AWS Inferentia. This role is critical for enabling large-scale AI/ML workloads. | Serve | 7 |
| Sr. Software Development Engineer, Amazon Quick Senior Software Development Engineer role focused on building AWS AI services using ML and LLM technologies within the Information Retrieval space. The role involves designing, developing, testing, and deploying distributed ML systems and large-scale solutions, with a focus on inference and serving infrastructure for AI services. | Serve | 7 |
| Sr. Software Development Engineer, Amazon Quick Senior Software Development Engineer role focused on building AWS AI services using ML and LLM technologies within the Information Retrieval space. The role involves designing, developing, testing, and deploying distributed ML systems and large-scale solutions, with a focus on inference and serving infrastructure for AI services. | Serve | 7 |
| Sr. Software Development Engineer, Amazon Quick Senior Software Development Engineer role focused on building AWS AI services using ML and LLM technologies within the Information Retrieval space. The role involves designing, developing, testing, and deploying distributed ML systems and large-scale solutions, with a focus on inference and serving infrastructure for AI services. | Serve | 7 |
| Software Engineer II, Quick, Amazon Quick Software Development Engineer II role at Amazon, focusing on building AWS AI services that leverage ML and LLM technologies within the Information Retrieval space. The role involves designing, developing, testing, and deploying distributed ML systems and large-scale solutions, collaborating on strategy and roadmap, and driving system architecture. It emphasizes working with new ML technologies on a high-visibility product. | Serve | 7 |
| Software Engineer II, Quick, Amazon Quick Software Development Engineer II role at Amazon, focusing on building AWS AI services that leverage ML and LLM technologies within the Information Retrieval space. The role involves designing, developing, testing, and deploying distributed ML systems and large-scale solutions, collaborating on strategy and roadmap, and driving system architecture. It emphasizes working with new ML technologies on a high-visibility product. | Serve | 7 |
| ML Compiler Engineer, Annapurna Labs Seeking a skilled compiler engineer to develop and optimize a deep learning compiler stack for AWS ML accelerators (Inferentia/Trainium), supporting frameworks like PyTorch, TensorFlow, and JAX for domains including LLMs and Vision. Responsibilities include compiler feature design, optimization, and collaboration with hardware, runtime, and framework teams. | Serve | 7 |
| Sr. Software Development Manager - Performance and Tooling, AWS Neuron, Annapurna Labs This role is for a Sr. Software Development Manager leading a team of compiler engineers to develop, deploy, and scale a compiler targeting AWS Inferentia and Trainium chips. The focus is on optimizing performance, cost, and ease of use for the Neuron SDK, involving deep knowledge of resource management, scheduling, code generation, and optimization for various compute architectures. Experience with toolchains like LLVM/GCC and compiler internals is preferred. | Serve | 7 |
| Software Development Engineer, ML Systems Integration, Machine Learning Israel (MLIL) — Integration Validation Software Development Engineer focused on ML Systems Integration and Validation for next-generation ML accelerator servers. The role involves owning CI/CD pipelines, test frameworks, and system-level validation for an ML inference accelerator platform, with a focus on LLM inference workloads. | Serve | 7 |
| Senior Software Engineer - AI/ML, AWS Neuron Inference Senior Software Engineer focused on optimizing LLM inference performance on AWS Neuron accelerators, working on core building blocks like Attention, MLP, Quantization, and Speculative Decoding. Collaborates with chip architects and compiler engineers to extract maximum performance and accuracy. | Serve | 7 |
| Sr. Delivery Consultant - AI/ML, AWS Professional Services Senior Delivery Consultant for AWS Professional Services, focusing on designing, implementing, and managing GenAI and ML solutions for customers. The role involves technical guidance, collaboration with stakeholders, and advising on AI/ML trends and technologies, with a strong emphasis on AWS services. | ServePost-train | 7 |
| Sr. Software Dev Engineer, Amazon Music Catalog Senior Software Development Engineer role focused on building and scaling GenAI and ML solutions within the Amazon Music Catalog team. The role involves developing, deploying, and optimizing LLMs in production, working with distributed systems and data pipelines, and partnering with Applied Scientists and Product Managers to integrate AI-driven capabilities into catalog systems. | ServePost-train | 7 |
| Software Development Engineer, CreativeX Software Development Engineer (MLE) for the CreativeX RAPID team at Amazon, focusing on real-time ad personalization and insights. The role involves tailoring visual ad experiences using technologies like latent diffusion models, LLMs, RL, and computer vision to provide dynamically optimized creatives with low latencies. Responsibilities include investigating new generative AI technologies, prototyping, evaluating feasibility, building data pipelines, and developing platforms for ML model deployment. | ServePost-train | 7 |
| Applied Scientist, Neuron ARG, Annapurna ML Applied Scientist role focused on the intersection of AI and program analysis for a deep learning compiler stack, optimizing models for ML accelerators like Trainium. Responsibilities include designing, developing, and deploying analyzers, architecting tooling, and publishing research in compiler technology and deep learning systems software. | Serve | 7 |
| Applied Scientist II - AMZ27057.1 The Applied Scientist II role at Amazon focuses on the design, development, evaluation, deployment, and updating of data-driven models and analytical solutions for ML and NL applications. The role involves applying statistical modeling, optimization, and ML techniques, routinely building and deploying ML models, and researching novel ML approaches. Mentoring junior scientists is also part of the responsibilities. The basic qualifications require a Master's degree or equivalent with one year of experience, or a Bachelor's degree with five years of experience, in a related field, with specific experience in programming (Java, C++, Python) and developing supervised/unsupervised ML models. | Serve | 7 |
| Machine Learning Engineer, Ad Response Prediction Machine Learning Engineer at Amazon Ads focused on Sponsored Products and Brands, re-imagining advertising with generative AI. The role involves designing, coding, and supporting scalable ML pipelines and online serving systems, optimizing ML model performance and infrastructure, and implementing end-to-end solutions. It requires driving technical direction, building and growing teams, and collaborating on product direction. The team operates on a large product catalog with strict latency constraints and works with research scientists to deliver relevant ads. | ServePost-train | 7 |
| Sr. Startup Solution Architect, GenAI , AWS Startups Frontier AI This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on providing architectural guidance, supporting the adoption of AWS services, and acting as a technical advisor to help startups build scalable, reliable, and secure solutions. | ServePost-train | 7 |
| Sr. Startup Solution Architect, GenAI , San Francisco GenAI Startups This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on architecting scalable, reliable, and secure solutions, supporting the adoption of AWS services, and providing feedback to product teams. The role also involves creating technical content and presenting at events. | ServePost-train | 7 |
| Sr. Delivery Consultant - AI/ML, AWS Professional Services This role is for a Senior Delivery Consultant focused on AI/ML solutions within AWS Professional Services. The consultant will design, implement, and manage AWS-based AI/ML applications and models for customers, providing technical guidance and support throughout the project lifecycle. Key responsibilities include gathering requirements, proposing model training and deployment strategies, and acting as a trusted advisor on AI/ML trends. The role requires experience with AWS AI/ML services and deploying LLMs in production. | ServePost-train | 7 |
| Sr. Startup Solution Architect, GenAI , San Francisco GenAI Startups This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on architecting scalable, reliable, and secure solutions, supporting the adoption of AWS services, and providing feedback to product teams. The role also involves creating technical content and presenting at events. | ServePost-train | 7 |
| Sr. Startup Solution Architect, GenAI , AWS Startups Frontier AI This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on providing architectural guidance, supporting the adoption of AWS services, and acting as a technical advisor to help startups build scalable, reliable, and secure solutions. | ServePost-train | 7 |
| Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs Senior Software Engineer role focused on building and optimizing the AWS Neuron compiler for AWS Inferentia and Trainium chips. The role involves transforming ML models (PyTorch, TensorFlow, JAX) into optimized implementations for deep learning workloads, with a focus on large language models and vision transformers. Responsibilities include compiler optimization, working with chip architects, and contributing to open-source communities. | Serve | 7 |
| Software Development Engineer, Alexa Audio Software Development Engineer role focused on integrating Generative AI and LLM capabilities into Alexa's audio experiences. The role involves designing and implementing software, creating infrastructure for LLMs in audio, developing tools to evaluate and improve model accuracy, reducing latency, and influencing operational excellence for audio services. It also includes mentoring junior engineers and contributing to hiring efforts. | ServePost-train | 7 |
| Systems Development Engineer (AWS Generative AI & ML Servers), AWS HW Engineering This role focuses on building and operating AWS cloud infrastructure specifically for AI training and inference workloads. The Systems Development Engineer will design, deliver, and operate server solutions that enable high performance and scalability for AI/ML and HPC. The role involves creating automation through agentic workflows and implementing AI-driven tools, impacting both AI implementation and core architecture within the AWS Hardware Engineering team. | Serve | 7 |
| Software Dev Engineer Machine Learning Software Development Engineer Machine Learning role focused on improving video and audio streaming experience for smart home devices. The role involves optimizing ML/AI frameworks for real-time inference, optimizing training pipelines, analyzing model performance, and leveraging GenAI tools for development productivity. It requires experience with video/image processing, computer vision, machine learning, and cloud computing, with a focus on scalable services and distributed systems. | Serve | 7 |
| Senior Software Development Engineer Senior Software Development Engineer role focused on developing advanced robotics systems at Amazon scale, integrating cutting-edge AI, control systems, and mechanical design for adaptable automation solutions. The role involves leading a team to design and implement a software framework for generalized dexterous mobile manipulation, including cloud and on-edge inferencing, real-time teleoperation, and human-machine interfaces. | ServeAgent | 7 |
| (Fall 2026) Annapurna Labs at AWS Internship (US) - Machine Learning Systems & Silicon Innovation Internship role focused on building AI infrastructure and ML systems, including custom silicon design, framework optimization, compiler development, and distributed training systems for AWS. | Serve | 7 |
| Software Development Engineer, CreativeX Software Development Engineer focused on real-time ad personalization and insights, leveraging generative AI technologies like latent diffusion models, LLMs, and RL to tailor visual ad experiences. The role involves investigating new technologies, building data pipelines, and developing platforms for ML model deployment in the Dynamic Creative Optimization (DCO) domain. | ServePost-train | 7 |
| Software Dev Engineer, EC2 Nitro Software Development Engineer on the EC2 Nitro Machine Learning Systems team, focusing on building and optimizing performance measurement infrastructure for AI/ML workloads. The role involves establishing best-known configurations, translating performance insights into technical requirements, and analyzing training/inference performance across accelerated platforms. It requires expertise in low-level systems, ML frameworks, and serving layers. | Serve | 7 |
