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. 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. | Serve |
| 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 |
| 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 |
| Applied Scientist II - AMZ9890756 Applied Scientist II role focused on designing, developing, evaluating, and deploying data-driven models and analytical solutions for ML/NL applications. The role involves applying statistical modeling, optimization, and ML techniques, researching new approaches, and mentoring junior scientists. Requires a Master's degree and experience in ML model development and deployment. | ServePost-train | 7 |
| AI Platform Data Engineer, Ring Decision Science, Ring Decision Science The AI Platform Data Engineer will focus on developing Platforms and Agentic AI solutions, leveraging AI at every layer of the data stack. This role involves building and maintaining data pipelines, curated datasets for AI/ML, and AI-native self-service data platforms using an AI-first development methodology. The engineer will use AI to build AI infrastructure, automate processes, and create self-improving systems. | ServeAgent | 7 |
| Senior Software Engineer, Annapurna Labs Senior Software Engineer to lead the development of machine learning tools for AWS Inferentia and Trainium ML accelerators. The role involves designing, developing, and operating a next-generation AI workload orchestration platform on Kubernetes, enabling scalable job scheduling, distributed training, and artifact management. Responsibilities include architectural decisions across the full stack, collaboration with ML researchers and hardware teams, mentoring engineers, and improving developer velocity. The focus is on optimizing hardware utilization and enabling large-scale training and inference jobs on custom AI silicon. | ServeAgent | 7 |
| Principal Firmware Engineer, Annapurna Labs ML Acceleration Systems Software This role is for a Principal Firmware Engineer focused on ML acceleration systems software within Amazon's Annapurna Labs. The engineer will lead a team in developing and deploying server firmware for millions of accelerators, using AI-driven tooling to diagnose and mitigate failures. The role involves close collaboration with hardware and software teams, establishing scalable operational procedures, and ensuring the reliability of systems used for machine learning workloads. | 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 |
| Applied Scientist II - AMZ9735083 Applied Scientist II role at Amazon focusing on the design, development, evaluation, and deployment of data-driven models and analytical solutions for ML and NL applications. The role involves applying statistical modeling, optimization, and ML techniques, researching and implementing novel approaches, and mentoring junior scientists. Requires a Master's degree and one year of experience in ML model development or a related field, with proficiency in programming languages like Python and experience with supervised and unsupervised learning. | 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 |
| Applied Scientist III - AMZ9898484 Applied Scientist III at Amazon to participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques, optimization methods, and other ML techniques. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. | ServePost-train | 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 |
| Applied Scientist II - AMZ9970940 Applied Scientist II role focused on designing, developing, evaluating, and deploying data-driven models and analytical solutions for ML and NL applications. This involves applying statistical modeling, optimization, and ML techniques, researching novel approaches, and building/deploying ML models. The role also includes mentoring junior engineers and scientists. | Serve | 7 |
| Sr. Software Development Engineer, Amazon Quick Senior Software Development Engineer role at Amazon 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, collaborating with experienced engineers and scientists, and influencing strategy and roadmap. It emphasizes working with the newest ML technologies on a high-visibility product. | 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 |
| Machine Learning - Compiler Engineer II, Annapurna Labs The Machine Learning Compiler Engineer II on the AWS Neuron team will support the development and scaling of a compiler for AWS Machine Learning accelerators (Inferentia and Trainium chips). This role involves architecting and implementing features for the AWS Neuron Software Development Kit (SDK), which optimizes neural network models for custom AWS hardware. The engineer will work with ML frameworks like PyTorch and TensorFlow, contributing to a toolchain aimed at improving ML performance. | 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 |
| Software Development Engineer, Alexa Connected Devices Software Development Engineer role focused on building and optimizing low-latency, scalable connectivity services for Alexa devices. The role involves integrating AI-driven capabilities and AI-powered features into these services, as well as leveraging AI-augmented development tools to accelerate the software development lifecycle. The team operates at a massive scale, handling billions of transactions daily, and is increasingly adopting an AI-first approach. | ServeAgent | 7 |
| Software Development Engineer, Alexa Audio Software Development Engineer role focused on enhancing Alexa's audio experiences by integrating Large Language Models (LLMs), improving model accuracy, reducing latency, and building scalable API platforms. The role involves designing, implementing, and delivering software features, creating infrastructure for LLM integration, and influencing the operational excellence roadmap for audio services. | ServePost-train | 7 |
| Software Development Engineer, Alexa Audio, Alexa Domains - Alexa Audio (Music) Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences, aiming to improve model accuracy and reduce latency. The role involves designing and delivering software, creating infrastructure for LLMs, developing tools for evaluation, and influencing the operational roadmap for core audio services. | ServePost-train | 7 |
| Software Development Engineer, Alexa Audio Software Development Engineer role focused on integrating Large Language Models (LLMs) 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, reduce latency, and influence the operational roadmap for core audio services. The position also requires mentoring junior engineers and contributing to hiring efforts. | ServePost-train | 7 |
| Software Development Engineer, Alexa Audio Software Development Engineer role focused on integrating Large Language Models (LLMs) 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, reduce latency, and influence the operational roadmap for core audio services. The position also requires mentoring junior engineers and contributing to hiring efforts. | ServePost-train | 7 |
| Software Development Engineer, Data Analytics Integration AI and Platform Excellence Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle. | Serve | 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 |
| Software Development Engineer, Alexa Audio, Alexa Domains - Alexa Audio (Music) Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences, aiming to improve model accuracy and reduce latency. The role involves designing and delivering software, creating infrastructure for LLMs, developing tools for evaluation, and influencing the operational roadmap for core audio services. | 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 |
| Software Development Engineer, Alexa Audio, Alexa Domains - Alexa Audio (Music) Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences, aiming to improve model accuracy and reduce latency. The role involves designing and delivering software, creating infrastructure for LLMs, developing tools for evaluation, and influencing the operational roadmap for core audio services. | 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 |
| Software Development Engineer, Alexa AI Developer Tech Software Development Engineer role focused on building and scaling core infrastructure for Alexa+, a generative AI-powered assistant. The role involves developing and maintaining features for LLM-based experiences, working on distributed systems with sub-ms latency at Amazon scale, and establishing architectural principles. | Serve | 7 |
| Software Development Engineer, Alexa AI Developer Tech Software Development Engineer role focused on building and scaling core infrastructure for Alexa+, a next-generation generative AI-powered assistant. The role involves developing and maintaining key system features supporting LLM-based experiences, working on distributed systems with sub-ms latency, and establishing architectural principles. | Serve | 7 |
| Software Development Engineer, Alexa AI Developer Tech Software Development Engineer role focused on building and scaling core infrastructure for Alexa+, a next-generation generative AI-powered assistant. The role involves developing and maintaining key system features supporting LLM-based experiences, working on distributed systems with sub-ms latency, and establishing architectural principles. | Serve | 7 |
| Software Development Engineer, Alexa AI Developer Tech Software Development Engineer role focused on building and scaling core infrastructure for Alexa+, a next-generation generative AI-powered assistant. The role involves developing and maintaining key system features supporting LLM-based experiences, working on distributed systems with sub-ms latency, and establishing architectural principles. | 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 |