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 |
|---|---|---|
| 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, optimizing compute for specific LLM training topologies, and working closely with hardware teams to maximize performance using C/C++. The goal is to scale AI compute across the data center for training frontier AI models. | Data | 9 |
| Principal PMT-ES - AI/ML Training, Annapurna Labs Principal Technical Product Manager to define and drive product strategy for training software on AWS Trainium, including distributed training libraries, post-training workflows (RLHF, DPO, fine-tuning), reinforcement learning frameworks, and training performance optimization. The role focuses on enabling researchers and operators to train frontier models at scale. | Data |
| 9 |
| Member of Technical Staff - Reinforcement Learning (Infrastructure), AGI Autonomy Develop training infrastructure for large-scale reinforcement learning on LLMs, working across the technology stack including ML systems, orchestration, and data management. Analyze, troubleshoot, and profile ML systems, and conduct MLSys research for new techniques and tooling. | DataAgent | 9 |
| Software Dev Engineer II, Stores Foundational AI -SFAI Software Development Engineer II focused on building generative AI for shopping experiences at Amazon. The role involves designing and implementing stable and efficient training systems for model training and reinforcement learning, collaborating with applied scientists and engineers to improve training efficiency, and developing scalable data infrastructure for Amazon-scale data ingestion and processing across training and evaluation stages. Requires experience with ML and LLM fundamentals, transformer architecture, and training/inference lifecycles. | DataPost-train | 8 |
| Software Development Manager, AWS Neuron SDK - Distributed Training This role focuses on engineering and optimizing distributed training for large-scale ML models, particularly LLMs with multi-modal inputs/outputs, on AWS Neuron accelerators. The primary goal is to enhance training resiliency and performance across thousands of nodes, ensuring Trainium devices are first-class citizens for ML acceleration. | DataServe | 8 |
| Member of Technical Staff - Data Platform Engineer, Frontier AI Robotics The role is for a Data Platform Engineer focused on building and maintaining the data infrastructure for robotics manipulation research at Amazon's Frontier AI Robotics team. This involves creating systems to process raw robot data into trainable datasets, including streaming ingestion, data curation, quality controls, and tools for researchers. The role requires full-stack development experience in a cloud-native environment and collaboration with researchers. | Data | 8 |
| 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 |
| 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 |
| Sr Applied Scientist - Robotics Simulation, Amazon Robotics R&D Senior Applied Scientist role focused on developing 3D physics-based simulation environments and tools for robotics, specifically for training large-scale machine learning models using reinforcement learning and synthetic data generation. The role involves establishing processes, building real-to-sim workflows, and minimizing sim-to-real gaps, with a secondary focus on enabling agentic systems through simulation. | DataAgent | 8 |
| Applied Scientist II The role focuses on developing and applying cutting-edge simulation methodologies for advanced robotics systems, including physics-based simulation, sim-to-real transfer, and machine learning. The goal is to enable rapid development, testing, and validation of robotic systems in complex environments. The role involves fundamental research and real-world development, translating research into scalable simulation capabilities that impact robot design and building. | DataAgent | 8 |
| Software Development Engineer, Applied AI Solutions Software Development Engineer role focused on building the platform for validating safety-critical autonomous systems. This involves designing scenario generation pipelines, integrating generative AI models for realistic behaviors, creating synthetic sensor data, and developing export connectors for simulation platforms. The role spans the full lifecycle from data curation to deployment monitoring, with a focus on automating testing and exploring edge cases. | DataAgent | 8 |
| Applied Scientist, AGI , AGI Information This role focuses on advancing knowledge graphs for the LLM era, specifically for LLM grounding and construction pipelines. It involves web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory over graphs. The primary responsibility is entity resolution for conflating facts from multiple sources into a single graph entity, requiring scalable, generic, and streaming data solutions. The role also touches upon agent memory, suggesting a secondary stage involvement. | DataAgent | 8 |
| 2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - United States, PhD Student Science Recruiting This internship focuses on developing systems and frameworks for machine learning asset lifecycle management, leveraging NLP and information retrieval. The role involves research into ML operations and knowledge engineering to enhance Amazon's ML capabilities. | DataPost-train | 8 |
| Neuron Collectives Software Engineer, Trainium Collectives Software Engineer role focused on enhancing collective algorithms and topologies for optimal AI training performance on Amazon's Trainium chips. This involves optimizing communication primitives to scale AI compute across data centers, working closely with hardware teams, and developing C/C++ implementations for training LLMs. | Data | 8 |
| SDE- ML Engineer, Frontier AI Robotics Machine Learning Systems Engineer for Frontier AI Robotics team, focusing on building and optimizing distributed training infrastructure for large-scale deep learning and transformer models. Role involves engineering scalable, high-performance systems for AI research and applications, with a focus on robotics, multimodal perception, and manipulation strategies. Requires strong software development, ML infrastructure, and deep learning framework expertise. | Data | 8 |
| Sr. SDE- ML Data Infrastructure, Frontier AI Robotics Senior Software Development Engineer focused on ML Data Infrastructure for Frontier AI Robotics at Amazon. The role involves building and maintaining scalable data infrastructure, designing dataset management systems, developing visualization tools, and implementing advanced data filtering techniques to support cutting-edge AI robotics research. Collaboration with science teams is key, requiring both infrastructure development and hands-on technical contribution to data preparation. | Data | 8 |
| Sr. SDE, Simulation, Frontier AI Robotics Seeking a Simulation Engineer to join an AI robotics research team, focusing on developing 3D physics-based simulation frameworks and tools to enable large-scale machine learning model training for robotics. The role involves developing simulations for reinforcement learning, closed-loop simulations, synthetic data generation, implementing robotics features, building real-to-sim workflows, and collaborating with ML researchers. | DataPost-train | 8 |
| Machine Learning Engineer, Neuro-Symbolic AI Labs Machine Learning Engineer responsible for designing the training and data pipeline strategy for ARG's ML efforts. | Data | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS This role focuses on designing and implementing modern data platforms, data pipelines, and enterprise RAG architectures within the healthcare and life sciences sector. The goal is to transform raw data into governed, AI-ready assets that support AI/ML model training and agentic AI systems, with a strong emphasis on regulatory compliance. | DataAgent | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS This role focuses on designing and implementing modern data platforms, data pipelines, and enterprise RAG architectures within the healthcare and life sciences sector. The goal is to transform raw data into governed, AI-ready assets that support AI/ML model training and agentic AI systems, with a strong emphasis on regulatory compliance. | DataAgent | 7 |
| Software Dev Engineer II, Alexa for Shopping Software Development Engineer II role focused on developing generative AI for shopping on Amazon, involving design and implementation of stable and efficient training systems for model training and reinforcement learning, collaboration with applied scientists and engineers to improve training efficiency and reliability, and design/implementation of scalable data infrastructure for Amazon-scale data ingestion, processing, and delivery across training and evaluation stages. Requires ML and LLM fundamentals. | DataPost-train | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS This role focuses on designing and implementing modern data platforms, architecting data pipelines, and building enterprise RAG architectures, vector stores, and knowledge graphs to enable AI agents and foundation models within the healthcare and life sciences industry. The consultant will work with complex data, regulatory requirements, and legacy systems to deliver production-grade data products for AI/ML model training and agentic systems. | DataAgent | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS This role focuses on designing and implementing modern data platforms, architecting data pipelines, and building enterprise RAG architectures, vector stores, and knowledge graphs to enable AI agents and foundation models to reason accurately within regulated healthcare environments. The goal is to ship production-grade data products for ML model training and agentic orchestration. | DataAgent | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS This role focuses on designing and implementing modern data platforms, data pipelines, and enterprise RAG architectures within the Healthcare and Life Sciences (HCLS) sector. The goal is to transform raw data into governed, AI-ready assets that support downstream applications like ML model training and agentic AI systems, all within regulated environments. | DataAgent | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS Senior Delivery Consultant specializing in Data for AWS Professional Services within the Healthcare and Life Sciences (HCLS) practice. The role focuses on building the data layer for AI-ready organizations, including designing and implementing modern data platforms, architecting data pipelines, and creating enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graphs. The consultant will work within regulated HCLS customer environments with complex data lineage and regulatory overlays, shipping production-grade data products for downstream consumers like ML model training and agentic orchestration. | DataAgent | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS This role focuses on designing and implementing modern data platforms, architecting data pipelines, and building enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graphs. The goal is to enable foundation models and AI agents to reason accurately and execute autonomously within regulated healthcare and life sciences environments. The role involves shipping production-grade data products for ML model training and agentic orchestration layers. | DataAgent | 7 |
| Sr. Software Development Engineer, MLOPs Senior Software Development Engineer focused on building and operating ML training infrastructure for robot learning at scale. This role involves designing and implementing distributed GPU training pipelines, CI/CD for ML models, experiment tracking, data pipelines for robotics datasets, and operationalizing novel ML models, with a focus on Kubernetes and large-scale distributed systems. | DataServe | 7 |
| Senior SDE, Prime Video Personalization & Discovery Senior Software Development Engineer on the Prime Video Data Platform team, focusing on building ML infrastructure for personalization and recommendation systems. The role involves end-to-end ownership of product, user experience, design, and technology, with a focus on big data pipeline architecture and scalable ML solutions. Responsibilities include designing and delivering ML and Data platform solutions, mentoring engineers, and influencing technical strategy. | DataServe | 7 |
| Reliability Analytics Engineer, Amazon Robotics This role focuses on reliability analytics within Amazon Robotics, leveraging AI/ML and data engineering to build and maintain assessment tools, data pipelines, and dashboards for robot fleet availability. The engineer will perform data cleansing, prepare reliability datasets, translate engineering questions into data queries, and develop automation for failure mode classification and fleet health monitoring. | Data | 7 |
| Data Engineer II, AAE Data Engineer II, AAE at Amazon AWS AI Services. This role focuses on building data platforms and intelligence infrastructure for AI services, including agentic AI. Responsibilities include designing and building end-to-end data platforms, ETL/ELT pipelines, agentic data workflows for automated reporting and insights, and executive dashboards. The role emphasizes data accuracy for revenue and financial reporting, and collaboration with various teams. It operates at the intersection of data engineering and agentic AI, supporting S-Team level visibility into AI revenue, adoption, and growth. | DataAgent | 7 |
| Sr. Software Development Engineer, Amazon Quick Senior Software Development Engineer to lead design and implementation of distributed AI data pipelines and large-scale systems for AWS AI services, focusing on ML and LLM technologies, Generative AI, and RAG. | Data | 7 |
| Principal Technical Program Manager, DC Power Utilization Management The Principal Technical Program Manager will lead data science and software initiatives within the DC power utilization management organization at AWS Infrastructure Services. This role focuses on driving high utilization in data centers through data science and machine learning, managing complex projects, and collaborating with various engineering teams to achieve capex efficiency and maintain high availability. | DataPost-train | 7 |
| Applied Scientist, Artificial General Intelligence - Data Services Applied Scientist role focused on dataset construction, training, and evaluating speech/language/other data for generative AI and LLMs at Amazon. Requires strong technical skills in NLP and ML, with experience in data sourcing, ground truth generation, normalization, and model building. | DataPost-train | 7 |
| Manager III, Software Dev, Search Science Data Infra The role is for a Manager III, Software Development within Amazon Search's Search Science Data Infrastructure team. The primary focus is on leading the development of services and infrastructure for ML model training data, feature engineering, and data quality monitoring. This involves managing the ML lifecycle and operations using AWS AI services and DL compute resources, and driving a scalable data-intensive infrastructure to enable data-driven ML services. The role also involves building training data systems for search ranking and matching models and providing technical leadership and mentorship. | Data | 7 |
| Senior Software Dev Engineer , Velocity Senior Software Engineer on the Velocity team at Amazon, focusing on perception and localization for autonomous robots. The role involves developing ML capabilities and infrastructure for perception/localization, optimizing algorithm performance, and building frameworks for data replay, analysis, and resource management on embedded systems. | DataServe | 7 |
| Software Engineer II, Search Science Data Infra The Software Engineer II, Search Science Data Infra role at Amazon focuses on building and managing infrastructure for ML model training data and feature stores. This involves developing services at the intersection of machine learning, big data, and distributed systems, managing the ML lifecycle, and processing large volumes of data for ML services. The role supports hundreds of science teams across Amazon and powers various search functionalities. | DataServe | 7 |
| 2026 Fall Research Science Internship - United States, PhD Student Science Recruiting This role is for a PhD student intern focused on research science at Amazon. The intern will apply advanced statistical techniques and AI/ML technologies to solve complex problems, implement prototypes, and work with large datasets. Responsibilities include data collection, analysis, interpretation, developing and testing hypotheses, documenting findings, and collaborating with team members. The role emphasizes hands-on scientific work, data analysis, experimental design, and computational modeling. | Data | 7 |
| Applied Scientist II, WW Sustainability This role focuses on building the AI/ML foundation for sustainability initiatives, involving data and AI/ML infrastructure implementation, data pipeline development, and establishing ML Ops best practices. The goal is to support various sustainability efforts like carbon footprinting and climate risk monitoring. | Data | 7 |
| Senior Applied Scientist , EC2 Optimization Science Senior Applied Scientist role focused on designing, implementing, and scaling decision-making algorithms for AWS EC2 capacity management. The role involves mathematical optimization, large-scale problem solving, and applying ML/Gen AI methods to enhance optimization algorithms. Responsibilities include data analysis, prescriptive optimization modeling, simulation, A/B testing, and collaborating with engineering and product teams. | Data | 7 |
| Software Engineer II, Search Science Data Infra Software Engineer II, Search Science Data Infra at Amazon, focusing on building and managing ML training data pipelines, feature stores, and infrastructure for Amazon Search. This role involves working with big data, distributed systems, and AWS AI services to support ML model training and inference for search ranking, matching, and personalization. | DataServe | 7 |
| Language Engineering Manager, AGI Data Services Manager for a Language Engineering team focused on data production and processing for AI and LLMs. Responsibilities include team leadership, technical guidance, process optimization, and collaboration with science and tech partners. | Data | 7 |
| Member of Technical Staff, Data Platform , AGI Backend engineer responsible for building and operating core services that ingest, process, and distribute large-scale, multi-modal datasets to internal tools and data pipelines for an AGI research lab. Focuses on designing backend architecture, defining operational standards, and ensuring production health, performance, and observability. | Data | 7 |
| Senior Language Engineer, Artificial General Intelligence - Data Services This role focuses on developing diverse datasets for training and evaluating AI models, utilizing synthetic data generation, model-based generation, and human-in-the-loop approaches. The Senior Language Engineer will define data creation strategies, lead complex data collections, and analyze large datasets. They will also build tools for data analysis and creation, and collaborate with scientists to evaluate AI model performance. | Data | 7 |
| Sr. SDE, MLA hardware/software co-design, Annapurna Labs Machine Learning Acceleration Senior Software Development Engineer focused on pre-silicon hardware/software co-development for next-generation machine learning chips (like Trainium) used in AWS. The role involves working with architecture, design, and emulation teams, writing bare-metal software and ML workloads to verify chip functionality and performance. | Data | 7 |
