ARA Program Rules

Last updated: March 26, 2025

By applying to or participating in the Amazon Research Awards Program (the “ARA Program”), you (defined below) agree to the following rules (“Rules”). These Rules are solely between Amazon.com, Inc. and its affiliates (“Amazon”, “we”, “us”, or “our”) and the entity that you represent (“you” or “your”), including the lead researcher/s who applies to the ARA Program (the “Principal Investigator”) and any members of the research team. Capitalized terms not defined herein may be defined in the AWS Agreements (as defined below). You and/or the Principal Investigator are responsible for distributing these Rules to all members of the research team before they participate in any research in connection with a proposal funded by the ARA Program.

I. Eligibility Requirements

To be eligible for an ARA Program award (“Award”), the Principal Investigator must be (1) either a full-time faculty member at an accredited academic institution or a permanent researcher at a non-governmental organization with recognized legal status in its country (equivalent to 501(c)(3) status under the United States Internal Revenue Code) and (2) at or above the age of majority in their jurisdiction of residence at the time of application. Each Principal Investigator is permitted to submit only one proposal to the ARA Program per call for proposal period.

By submitting your proposal to the ARA Program, you represent that your Principal Investigator:

(a) is not a paid employee of a government entity (other than an accredited academic institution);

(b) is not under US export controls or sanctions;

(c) has not been a director, officer, employee, intern or contractor of Amazon within the 12 months preceding submission of your proposal to the ARA Program (“Ineligible Personnel”);

(d) is not a member of the immediate family or household of Ineligible Personnel; and

(e) has not participated in or had decision-making authority over any cloud infrastructure procurements involving Amazon.

The ARA Program is void in Cuba, Iran, Syria, North Korea and the Crimea, Luhansk and Donetsk regions of Ukraine, and where otherwise prohibited by law.

Amazon employees, including employees of Amazon Web Services, Inc. (“AWS”), are not eligible to receive an Award.

Amazon is not responsible for your internal organizational policies and procedures that may restrict your (including the Principal Investigator’s) ability to submit a proposal to the ARA Program.

II. Application Content

No proposal to the ARA Program may contain any confidential information and no part may be marked as ‘confidential.’ Amazon does not accept any legal obligation (whether of confidentiality, compensation, return or otherwise) with respect to any proposals. Amazon reserves the right to implement competitive, similar, or identical ideas in the future, without restriction or obligation. You understand and acknowledge that Amazon has wide access to technology, designs, and other materials, and may work on and/or develop projects and ideas that may be competitive with, similar to, or identical to your proposal in theme, idea, format or other respects, inclusive. You acknowledge and agree that you will not be entitled to any compensation as a result of Amazon’s use of any such similar or identical material that has or may come to Amazon from other sources.

You represent and warrant that your proposal:

(a) is either your original work or an update to your original work;

(b) does not, to your knowledge, infringe any third-party patent rights; and

(c) does not, to your knowledge, infringe, misappropriate or otherwise violate any other third-party intellectual property rights (i.e., other than patent rights), including any copyrights, trade secrets, trademarks, contract or licensing rights, rights of publicity or privacy, or moral rights.

III. Awards

Proposals selected for funding will receive an Award that may include cash, Promotional Credit (as defined in the AWS Promotional Credit Terms & Conditions), or both. Award funding is not extendable or transferable without our written consent, but you may submit new proposals for subsequent ARA Program calls.

All Award amounts will be determined by Amazon in its sole discretion. Any cash component of an Award:

(a) will be structured as a one-time unrestricted gift to your Principal Investigator’s academic institution or organization;

(b) will be provided directly to your academic institution or organization for distribution and management; and

(c) may not be used for indirect expenses which are not allocable, reasonable, adequately documented, and consistent with established policies and practices of your academic institution or organization.

You are responsible for the administration and apportionment of any costs and expenses associated with an Award, including any allowable and allocable overhead or indirect costs. In order to process any cash Award, you will be required to complete administrative requirements, which may include submitting a W-9 form to us, completing a tax questionnaire, and registering in Amazon’s Payee Central System. If you do not fulfill the administrative requirements for processing cash Awards within two years of your receipt of an Award notification, Amazon reserves the right to withhold payment. Any payment from Amazon to you under the Award may be issued by a purchase order. Except where prohibited by law, you are responsible for all taxes (including income tax and value added tax) that may be imposed on you by relevant local tax authorities.

These Rules, the agreements referenced herein, and any other agreement regarding the relationship between you and Amazon will constitute a Master Agreement under the terms of the purchase order.

IV. AWS Customer Agreement and AWS Promotional Credit Terms & Conditions

Amazon may make available to you an amount of AWS promotional computing credits (“AWS Credits”) for use in support of this Agreement. AWS Credits provided to University under this Agreement are subject to the AWS Promotional Credit Terms and Conditions (as may be updated from time to time on the AWS website). You acknowledge and agree that any use of AWS services, including but not limited to use of AWS Credits, is subject to the terms and conditions set forth in the AWS Customer Agreement (https://aws.amazon.com/agreement/), and/or any separate, bespoke agreement that you have entered into with Amazon governing use of AWS services (collectively, the “AWS Agreements”). In the event of any conflict between this Agreement and the AWS Agreements, the terms of the AWS Agreements shall take precedence.

V. Privacy

You acknowledge and agree that we may collect, store, share, and otherwise use personally identifiable information provided during the ARA Program application process, including but not limited to, name, mailing address, phone number, and email address. All personally identifiable information collected is subject to, and will be used in accordance with, the Amazon Privacy Notice, including for administering the ARA Program and verifying applicants’ identities, addresses, and telephone numbers in the event a proposal is selected for funding. By participating in the ARA Program, you consent to the transfer of personal data to the United States for purposes of administering the ARA Program, conducting publicity about the ARA Program, and additional purposes that are consistent with goals relating to the ARA Program. The data controller for information collected by us is Amazon.com, Inc., 410 Terry Ave North, Seattle, Washington 98109, USA.

VI. Publicity

Except where prohibited, you consent to our use of your name and the Principal Investigator’s name and title, proposal title, and proposal abstract text for purposes of identifying Amazon’s support of you, the Principal Investigator, the proposal and/or the ARA Program.

You may acknowledge our support by stating that your research is supported by the ARA Program (e.g., “Research reported in this [publication/press release] was supported by an Amazon Research Award, [Cycle /Year].”). Any use of Amazon or AWS logos is subject to the Amazon Trademark Guidelines and AWS Trademark Guidelines, respectively. Any other use of Amazon or AWS logos requires Amazon’s or such affiliate’s prior written consent. You must receive Amazon’s prior written consent before issuing a press release or making any public disclosure regarding your participation in the ARA Program. You agree not to misrepresent or embellish the relationship between us and you. You will not imply any relationship or affiliation between us and you except as expressly permitted by these Rules.

VII. Limitation of Liability

TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU ACCEPT THE CONDITIONS STATED IN THESE RULES, AGREE TO BE BOUND BY THE DECISIONS OF AMAZON, AND WARRANT THAT YOU ARE ELIGIBLE TO PARTICIPATE IN THE ARA PROGRAM. TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU, EACH RESEARCH TEAM MEMBER, THE PRINCIPAL INVESTIGATOR AND THE PRINCIPAL INVESTIGATOR’S INSTITUTION HEREBY RELEASES AMAZON FROM, AND WAIVES ANY AND ALL CLAIMS AGAINST AMAZON FOR, ANY LOSSES, LIABILITY, AND DAMAGES OF ANY KIND, (INCLUDING FOR ANY LOSS OF DATA, LOST PROFITS, COST OF COVER OR OTHER SPECIAL, INCIDENTAL, CONSEQUENTIAL, INDIRECT, PUNITIVE, EXEMPLARY OR RELIANCE DAMAGES) INCURRED OR SUSTAINED IN CONNECTION WITH OR ARISING OUT OF (1) THE ARA PROGRAM OR ANY TRAVEL OR ACTIVITY RELATED THERETO, (2) USE OF ANY PROPOSAL OR RIGHTS THEREIN, OR (3) ANY BREACH OF ANY AGREEMENT OR WARRANTY ASSOCIATED WITH THE ARA PROGRAM, INCLUDING THESE RULES, HOWEVER CAUSED AND REGARDLESS OF THEORY OF LIABILITY.

VIII. Changes

We may amend any of these Rules at our sole discretion by posting the revised terms on the ARA Program website. Your continued participation in the ARA Program after the effective date of the revised Rules constitutes your acceptance of the rules.

IX. Disputes

Any dispute or claim relating in any way to the ARA Program will be resolved in accordance with terms set forth in the AWS Agreements.

X. Representations and Warranties

You represent and warrant that:

(a) your receipt of any Award is neither prohibited by nor inconsistent with any applicable laws, regulations, or binding orders, including applicable ethics rules or internal institutional rules;

(b) you have completed or will complete all legal and ethical requirements necessary to accept the Award;

(c) your receipt of the Award will not knowingly create a conflict of interest for Amazon;

(d) the Principal Investigator has not participated in, nor had, and do not anticipate participating in or having, any decision-making authority over, any procurements or purchasing decisions involving Amazon on behalf of your organization during the previous or upcoming twelve (12) months; and

(e) you will properly book and record the Award in your accounting documents in accordance with applicable laws and regulations.

In the event that your representations and warranties under this section are or become inaccurate, you must notify us immediately (research-awards@amazon.com) and any Award your organization receives will be voidable.

US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scalable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Research Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the intersection of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, WA, Seattle
Amazon has co-founded and signed The Climate Pledge, a commitment to reach net zero carbon by 2040. As a team, we leverage GenAI, sensors, smart home devices, cloud services, material science, and Alexa to build products that have a meaningful impact for customers and the climate. In alignment with this bold corporate goal, the Amazon Devices & Services organization is looking for a passionate, talented, and inventive Senior Applied Scientist to help build revolutionary products with potential for major societal impact. Great candidates for this position will have expertise in the areas of agentic AI applications, deep learning, time series analysis, LLMs, and multimodal systems. This includes experience designing autonomous AI agents that can reason, plan, and execute multi-step tasks, building tool-augmented LLM systems with access to external APIs and data sources, implementing multi-agent orchestration, and developing RAG architectures that combine LLMs with domain-specific knowledge bases. You will strive for simplicity and creativity, demonstrating high judgment backed by statistical proof. Key job responsibilities As a Senior Applied Scientist on the Energy Science team, you'll design and deploy agentic AI systems that autonomously analyze data, plan solutions, and execute recommendations. You'll build multi-agent architectures where specialized AI agents coordinate to solve complex optimization problems, and develop tool-augmented LLM applications that integrate with external data sources and APIs to deliver context-aware insights. Your work involves creating multimodal AI systems that synthesize diverse data streams, while implementing RAG pipelines that ground large language models in domain-specific knowledge bases. You'll apply advanced machine learning and deep learning techniques to time series analysis, forecasting, and pattern recognition. Beyond technical innovation, you'll drive end-to-end product development from research through production deployment, collaborating with cross-functional teams to translate AI capabilities into customer experiences. You'll establish rigorous experimentation frameworks to validate model performance and measure business impact, building AI-driven products with potential for major societal impact.
US, CA, San Francisco
Amazon launched the AGI Lab to develop foundational capabilities for useful AI agents. We built Nova Act - a new AI model trained to perform actions within a web browser. The team builds AI/ML infrastructure that powers our production systems to run performantly at high scale. We’re also enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities This role will lead a team of SDEs building AI agents infrastructure from launch to scale. The role requires the ability to span across ML/AI system architecture and infrastructure. You will work closely with application developers and scientists to have a impact on the Agentic AI industry. We're looking for a Software Development Manager who is energized by building high performance systems, making an impact and thrives in fast-paced, collaborative environments. About the team Check out the Nova Act tools our team built on on nova.amazon.com/act
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Applied Scientist III Job Location: Seattle, Washington Job Number: AMZ9674037 Position Responsibilities: 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 (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. 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. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $167,100/year to $226,100/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000
IN, KA, Bengaluru
Amazon Health Services (One Medical) About Us: At Health AI, we're revolutionizing healthcare delivery through innovative AI-enabled solutions. As part of Amazon Health Services and One Medical, we're on a mission to make quality healthcare more accessible while improving patient outcomes. Our work directly impacts millions of lives by empowering patients and enabling healthcare providers to deliver more meaningful care. Role Overview: We're seeking an Applied Scientist to join our dynamic team in building state of the art AI/ML solutions for healthcare. This role offers a unique opportunity to work at the intersection of artificial intelligence and healthcare, developing solutions that will shape the future of medical services delivery. Key job responsibilities • Lead end-to-end development of AI/ML solutions for Amazon Health organization, including Amazon Pharmacy and One Medical • Research, design, and implement state-of-the-art machine learning models, with a focus on Large Language Models (LLMs) and Visual Language Models (VLMs) • Optimize and fine-tune models for production deployment, including model distillation for improved latency • Drive scientific innovation while maintaining a strong focus on practical business outcomes • Collaborate with cross-functional teams to translate complex technical solutions into tangible customer benefits • Contribute to the broader Amazon Health scientific community and help shape our technical roadmap
US, MA, Boston
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.
US, CA, Santa Clara
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. As part of our diverse team—including data scientists, engineers, language engineers, linguists, and program managers—you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence. Key job responsibilities In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. Specific responsibilities include: * Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features * Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings * Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases * Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance * Develop and refine annotation guidelines and quality frameworks for evaluation tasks * Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies * Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements * Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts * Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.