This role focuses on designing and building "agent-ready" data platforms that enable AI agents to autonomously search, process, and analyze data. It involves advising customers on modern data strategies including RAG, semantic search, and natural language data exploration, while also leveraging traditional data analytics, search, and streaming services. The role requires deep technical expertise in the data lifecycle and adjacent domains like ML and security, with a strong emphasis on cloud-native and generative AI-native reference architectures.

This role is for a Senior AI Specialist Solutions Architect at AWS, focusing on helping customers adopt and scale GenAI/ML and Agentic technologies. The architect will build technical relationships, provide architectural guidance on security, cost, performance, and operational efficiency, and act as a voice of the customer internally. Responsibilities include crafting scalable architectures, creating technical content, and leading deep dives and workshops. The role requires experience in designing and implementing production AI systems, including LLMs, multi-modal FMs, fine-tuning, inference, RAG, FM evaluation, Vector DBs, Agentic workflows, and MLOps, with hands-on experience in AWS ecosystems like Bedrock, AgentCore, and SageMaker. Experience in regulated environments is preferred.

Senior AI/ML Solution Architect for ANZ Public Sector, focused on driving customer adoption of AI/ML services, including agentic and traditional ML, and MLOps best practices. The role involves deep technical engagement, helping customers modernize their AI/ML practices and build AI-driven solutions.

This role focuses on designing and building AI-integrated applications and re-engineering existing applications to leverage AWS Cloud services. The Sr. Application Architect will guide customers through the AI Development Life Cycle, design Generative AI and Agentic AI architectures, and advise on responsible AI practices. The role involves working with AWS AI services like Bedrock, SageMaker, and Amazon Q, and emphasizes cloud-native application development.

This role focuses on securing AI/ML workloads, including Generative AI, LLMs, and agentic AI systems, for AWS customers. The Cloud Security Architect will assess and mitigate security risks, design security architectures with guardrails and access controls, and advise on responsible AI governance. The role requires strong programming skills and experience with AWS security services, as well as a growing proficiency in securing AI applications, RAG pipelines, and agentic systems.

Solutions Architect for Financial Services & Insurance (FSI) customers in India, focusing on advising them on adopting and leveraging AWS cloud technology and GenAI. The role involves designing customer solutions, architecting solutions with AWS technology, serving as a thought leader, capturing and sharing best practices, identifying customer requirements, and acting as a trusted advisor. Requires experience in building large-scale AI/ML solutions, deploying LLMs in production, and hands-on experience with AWS AI/ML services like Bedrock, AgentCore, and SageMaker, including RAG implementation. Agentic AI expertise with multi-agent orchestration, tool use, memory, and guardrails is preferred, as is expertise in architecting AI systems in regulated environments.

AWS Professional Services is seeking an AI/ML Architect to help public sector clients in Canada adopt and implement ML and Generative AI solutions. The role involves understanding business challenges, designing and building solutions using AWS ML services, and collaborating with engineering teams to bring them to production. Experience with ML/GenAI development, AWS ML services, and project lifecycle support is required.

Senior Software Development Engineer to create autonomous AI security solutions for Amazon, leveraging AI/ML to automate threat detection, analysis, and remediation. The role involves architecting, designing, and developing these systems, building scalable applications, and mentoring a new team to enhance Amazon's security posture.

This role leads the Learning Architecture team at AWS Training & Certification, focusing on building the knowledge layer for AI agents that power personalized learning experiences. The team owns strategy, roadmap, and execution for systems like persona frameworks, skills, assessment architecture, and quality rubrics. The role involves managing a team of Learning Architects and collaborating with Applied Science and Engineering to define AI capabilities, drive quality at scale through a Quality & Rubric Engine, and govern the AWS skill taxonomy. Experience in people management and building products with Agentic AI is required.

Data Scientist role focused on building AI capabilities for financial planning and analysis (FP&A) at Amazon. The role involves developing forecasting models and AI systems, including agents, to automate repetitive finance tasks. The models ship to production and influence key financial decisions like stock-based compensation and headcount planning. Responsibilities include applying data science methodologies, leading model lifecycles from research to production, conducting experiments, and partnering with stakeholders.

The role focuses on building Generative AIUX products for AWS customers, specifically an AI-powered internal prototyping tool (Venue) and an external version (Arena). It involves integrating with LLMs, optimizing AI-driven interfaces, and designing end-to-end GenAI-powered services for design generation, validation, and automation.

This role focuses on helping enterprise customers adopt and implement Generative AI, Machine Learning, and Agentic technologies on AWS. The Solution Architect will act as a trusted advisor, building technical relationships, and crafting scalable architectures to address customer challenges. Responsibilities include guiding customers through GenAI/ML and Agentic projects, providing recommendations on various aspects of cloud architecture, advocating for customer needs internally, and creating technical content and best practices. The role requires hands-on experience with AWS AI services, LLM deployment, and RAG implementation.

This role focuses on designing and building agentic AI systems for security automation within Amazon. The scientist will reason about code, produce security intelligence, and adapt AI/ML techniques to solve security problems, ultimately contributing to the development of secure software at scale.

Software Development Engineer II for AWS User Experience Products & Platform team, focusing on building an intelligent, agent-powered system to automate and accelerate AWS Management Console development. The role involves designing and architecting a multi-agent system leveraging LLMs, tool-use, and autonomous reasoning to generate, validate, and deploy console experiences.

Senior Product Manager for Amazon Business India, focusing on new customer acquisition and traffic. The role involves defining product strategy and roadmap, leveraging ML and Generative AI for targeting, personalization, and conversational experiences. It also includes building verification systems and a cross-store shopping experience, requiring close collaboration with engineering, science, and marketing teams.

Applied Scientist II role focused on building and deploying Generative AI and Machine Learning solutions for Amazon Private Brands' product assortment, pricing, and merchandising. The role involves adapting state-of-the-art research, inventing novel solutions, developing prototypes, and implementing production software, with a focus on agentic AI and large language models. Responsibilities include partnering with business stakeholders, adapting ML solutions, inventing and deploying novel science solutions, reviewing team's work, and publishing research.

Senior Software Development Engineer for Amazon Robotics' Vulcan program, focusing on motion behaviors for robotic manipulation. The role involves designing and building software infrastructure, observability tools, and ML training/deployment pipelines for production robot systems. It sits at the intersection of robotics, ML systems, and production engineering, requiring experience in C++, Python, and building reliable, scalable systems in complex real-time domains.

Applied Science Manager to lead a team focused on understanding and optimizing how advertising creates value for shoppers and selling partners, particularly as the shopping experience evolves towards agentic commerce. The role involves leading research, designing experiments, developing optimization algorithms, and translating research into production systems, with a strong emphasis on causal inference, economic modeling, and applied ML.

The Data Scientist will develop risk and reliability models for network availability using telemetry data, build operational analytics and dashboards, and design experiments to evaluate automation, including agentic systems. The role focuses on providing evidence for decisions, measuring outcomes of operational changes, and improving data quality for availability programs.

The Customer Solutions Manager (CSM) for AWS's Aerospace & Satellite team advises aerospace and satellite organizations on cloud adoption and AI transformation. The role involves guiding customers through multi-year cloud adoption, migration, modernization, and AI transformation initiatives, focusing on deploying agentic AI workflows, building generative AI assistants, modernizing telemetry and command platforms, and accelerating launch readiness with intelligent automation. The CSM acts as a trusted advisor and central connector between customers and AWS teams, driving execution and identifying opportunities for AI/ML capabilities in space data processing and autonomous operations.

Software Development Engineer II on the 3P Seller Tools and Gen AI Solutions team, building internal tools and external solutions powered by cloud computing and generative AI for 3P Sellers. The role focuses on agentic AI and distributed systems, creating new products and services from the ground up.

This role focuses on developing AI/ML products and scalable analytics applications for operations optimization. Key responsibilities include AI Agent development for data analytics, applying statistical and ML techniques, developing science-based Supply Chain solutions, and working with LLMs to automate processes. The role involves creating and maintaining data infrastructure for advanced analytics and ML solutions, with a focus on optimizing operations across various global regions.

This role focuses on developing and enhancing mathematical optimization models for supply chain planning, specifically for Amazon's North American network. It involves building intelligent agents using Agentic and Generative AI to automate planning workflows, make model outputs interpretable, and run network simulations. The role also includes collaborating with software engineering to productionalize models on AWS infrastructure and designing metrics for performance evaluation.

Software Development Engineer role focused on building and improving automated, algorithmic solutions using machine learning, computer vision, and robotics to prevent, detect, and correct inventory issues in Amazon's fulfillment centers. The role involves building new software services and tools, designing production systems, and working with research scientists on next-generation intelligent systems.

Software Development Engineer role focused on applying Generative AI and Large Language Models to enhance advertising experiences on Amazon's shopping surfaces at massive scale. The role involves designing, developing, and operating large-scale distributed systems, optimizing data pipelines, and collaborating with scientists and product managers to deliver personalized, context-aware advertising solutions.

This role focuses on helping AWS customers design, build, and productionize AI agentic systems using services like Amazon Bedrock and AgentCore. It involves direct customer engagements, developing reusable assets and open-source contributions, and influencing AWS service roadmaps. The role requires a blend of engineering, advisory, and product influence, with a strong emphasis on customer outcomes and responsible AI practices.

Senior Prototyping Architect for a new AGS Security Engineering team focused on building secure solutions and prototypes for customers adopting generative AI and agentic architectures. The role involves hands-on building of security capabilities, developing secure reference patterns, and enabling the broader field to build securely. It emphasizes working with emerging technologies and evolving secure engagement practices.

Applied Scientist II role focused on building machine learning models and algorithms for the Last Mile delivery experience, involving mapping, location, sensor data pattern detection, and computer vision. The role requires driving designs from ideation to production, with an emphasis on building v1 products autonomously.

Software Development Engineer II role at AWS focused on building foundational customer intelligence for go-to-market teams. The role involves designing and delivering solutions that combine distributed big data technologies and agentic AI development, with a focus on data ingestion, scalable systems, and ML-optimized data foundations for RAG, recommendation engines, and predictive models. The engineer will also work with inference capabilities and apply ML to solve data problems.

Senior Business Intelligence Engineer to build AI-native data products for Amazon Devices, architecting semantic and contextual layers for AI agents to reason over business data. Responsibilities include data pipelines, MCP servers, semantic layers for AI agents, AI-powered automation for business workflows, and evaluating/integrating emerging AI/ML capabilities.

Senior ProServe Cloud Architect for Healthcare and Life Sciences at AWS, focusing on designing and implementing AI and cloud solutions for pharmaceutical customers. The role involves translating business objectives into technical solutions, guiding customers on industry trends and agentic AI, and collaborating with internal AWS teams to drive innovation and successful solution implementations.

This role is for a Sr. Manager of Software Development focused on building and delivering next-generation agentic AI technologies within Amazon's Devices organization. The role involves leading a team to create intelligent, scalable systems that unify enterprise tools and streamline data-driven decision-making, bringing AI-powered efficiency to the engineering ecosystem. The focus is on building and launching new AI services from the ground up, with a strong emphasis on agentic AI and its application in hardware engineering.

This role focuses on applying Generative AI, ML, and NLP to enhance customer service experiences within Amazon. The Applied Scientist will own the definition and implementation of AI-driven innovations, transforming business requirements into technology solutions. Key responsibilities include developing novel algorithms, analyzing data for insights, and collaborating with cross-functional teams to integrate models into production systems.

Software Development Engineer II role focused on building AI-powered learning solutions and content creation tools using generative AI and an agentic AI framework for Amazon's talent development ecosystem.

Software Development Engineer role focused on building and improving automated, algorithmic solutions using machine learning, computer vision, and robotics to prevent, detect, and correct inventory issues in Amazon's fulfillment centers. The role involves building new software services and tools, designing production systems, and working with research scientists on next-generation intelligent systems.

This role is for a Data and AI Cloud Architect on the AWS Professional Services team in Taiwan, focusing on the manufacturing and semiconductor industries. The architect will design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS, acting as a trusted technical advisor to enterprise customers. Key responsibilities include leading architecture design, building end-to-end data architectures, architecting AI/ML solutions using AWS services like SageMaker and Bedrock for industry-specific use cases, collaborating with stakeholders on data strategies, mentoring junior consultants, and developing reusable assets. The role also involves partnering with AWS teams, contributing to thought leadership, and staying current with data engineering, analytics, and generative AI trends. Basic qualifications include experience conveying technical concepts, a relevant degree or equivalent experience, 8+ years in data/cloud architecture with 5+ years on AWS, deep expertise in data platform technologies (Python, SQL, Spark, Scala), and fluency in Mandarin and English. Preferred qualifications include experience with large-scale transformation programs, domain expertise in manufacturing/semiconductor industries, knowledge of Industry 4.0, experience with generative AI architectures (RAG, fine-tuning, agents), and familiarity with Taiwan's data privacy regulations.

Product Manager for AWS FinOps Agent, focusing on building agentic workflows and defining the strategy for generative AI in cloud financial management. The role involves understanding customer needs, defining product vision, and collaborating with engineering and applied science teams to deliver autonomous FinOps experiences.

This role focuses on building the next generation of software verification tools by combining advances in AI, cloud computing, and formal verification techniques. The Principal Applied Scientist will define roadmaps, lead delivery of AI solutions, identify and implement new analysis capabilities, and explore generative AI for tasks like requirement formalization, test generation, and proof repair. The role involves using a combination of traditional formal methods and generative AI to solve complex code analysis problems.

Senior Product Manager for Alexa Canada, focusing on expanding Alexa's presence in the Canadian market. This role involves defining user needs, creating product roadmaps, understanding market dynamics (including emerging AI/ML), developing requirements, leading cross-functional teams, owning the customer experience, tracking launches, managing trade-offs, monitoring performance, and working closely with engineering. The role requires technical depth to evaluate AI model behavior and technical approaches, and a proactive exploration of new AI capabilities like large language models and agentic AI.

Principal Product Manager, Technical for Amazon Music's Agent Experience and Music Intelligence. This role defines the strategic vision for AI-powered music experiences across all Amazon Music product surfaces, focusing on cross-platform strategy, intelligence layer utilization, and emerging technologies like generative AI. The PM will influence senior leadership, partner across organizations, and translate complex technical capabilities into customer-facing product strategies with clear business cases.

Senior AI Solutions Architect for AWS, focusing on guiding enterprise customers in adopting and scaling GenAI/ML and Agentic technologies. The role involves building technical relationships, designing scalable architectures, providing technical leadership, and creating content like whitepapers and workshops. It requires hands-on experience with AWS AI services, implementing solutions including RAG, fine-tuning, inference, and agentic workflows, and a strong understanding of production AI systems.

Customer Engineer focused on building Agentic AI and multi-modal Generative AI applications and workflows for financial services customers on AWS. This role involves creating end-to-end solutions, prototypes, and modern data applications, with a strong emphasis on hands-on development with AWS AI services.

Principal Product Manager - Tech for Sponsored Products and Brands, focusing on advertiser-facing Gen AI products and conversational commerce. The role involves defining product vision, rethinking campaign management using LLMs, and collaborating with various teams to deliver intelligent, adaptive experiences. It requires deep Ad Tech expertise and the ability to influence across organizational boundaries.

This role focuses on building and delivering Generative AI solutions for customer-facing business problems using AWS services and open-source technology. Responsibilities include designing, developing, and evaluating solutions like RAG, multi-agent systems, and model fine-tuning, as well as providing guidance and creating best practices for customers. The role also involves analyzing data to optimize processes and identify investment opportunities.

Software Development Engineer II role focused on building the backend services for an AI-powered conversational agent (Amazon Marketing Cloud Assistant) that allows advertisers to interact with data using natural language. The role involves designing and building scalable data pipelines, LLM orchestration, prompt engineering, tool use, agent workflows, and contributing to the evaluation framework for agent accuracy. It operates at the intersection of LLMs, distributed systems, and large-scale advertising data.

This role is for a Sr. AI Solution Architect at AWS, focusing on helping customers adopt and scale GenAI/ML and Agentic technologies. The architect will build technical relationships, design scalable architectures, provide recommendations on various aspects of cloud adoption, and act as the voice of the customer internally. Responsibilities include creating technical content, leading deep dives, and contributing reusable assets. The role requires hands-on experience with AWS AI services, implementing RAG, fine-tuning LLMs, deployment, distributed inference, and MLOps.

Software Development Engineer II for the Amazon Lockers team, focusing on applying AI/ML to logistics and customer delivery problems. The role involves building AI-driven workflows, intelligent automation, predictive systems, and conversational experiences to enhance customer experience and operational efficiency. This is an engineering role focused on building and integrating AI technologies into existing and new product features.

Software Development Engineer II (SDE II) for Amazon Robotics Scanless Tech team, focusing on developing and deploying machine learning and computer vision based software technologies for robotics applications. The role involves building edge and cloud CV applications, leveraging AWS ML, optimizing fulfillment infrastructure, and partnering with Applied Scientists to develop ML applications. The team's solutions are core to the business and deployed at scale.