AWS Agentic AI is sponsored by Amazon Web Services (AWS). Aims to advance agentic AI research by funding development of open-source tools and research that benefit the AI community at large, or impactful research related to agents.

AWS Agentic AI call for proposals — Spring 2026 - Amazon Science Information and knowledge management Operations research and optimization Security, privacy, and abuse prevention Our scientific contributions Research from our scientists and collaborators. Our experts present and discuss cutting-edge research at scientific meetings globally.

Information and knowledge management Operations research and optimization Security, privacy, and abuse prevention Our scientific contributions Research from our scientists and collaborators. Our experts present and discuss cutting-edge research at scientific meetings globally. The latest from Amazon researchers Technical deep-dives and perspectives from our scientists.

Research milestones and recent achievements. The latest from Amazon researchers Technical deep-dives and perspectives from our scientists. Research milestones and recent achievements.

Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Meet the team building useful AI agents.

Try Amazon’s frontier foundation models. Meet the team building useful AI agents. Try Amazon’s frontier foundation models.

Faculty research opportunities on industry-scale technical challenges. Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. Faculty research opportunities on industry-scale technical challenges.

Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. AWS Agentic AI call for proposals — Spring 2026 Advancing the frontiers of AI. By Amazon Research Awards team AWS offers a broad and deep set of tools for businesses to create impactful AI solutions faster.

Our mission is to share our learnings and AI capabilities as fully managed services, and put them into the hands of every scientist and developer. AWS Agentic AI aims to advance agentic AI research by funding development of open-source tools and research that benefit the AI community at large, or impactful research related to agents.

We seek proposals related to agentic AI in the areas below: Development and application of no-code / low-code solutions for agentic AI, which facilitate the rapid deployment and management of AI agents at scale AI-enhanced productivity applications, which enable seamless human-AI collaboration and improve automation Multi-agent systems and collaborations, which enable agents to work together securely and effectively Agentic AI for accelerating scientific discoveryin fields including but not limited to health & life sciences, chemistry, materials science, and physics Other topics related to agentic AI development and applications are also welcome, including, but not limited to: Safety and responsible AI for agentic behavior Agent customization, involving post-training the execution model or optimization of prompts, tools, specs, steering files, etc. outside of the model Access methods for data integration and retrieval systems, e.g., vector, lexical, graph, relational, hybrid Enterprise-scale agent operations and governance Application domains, including but not limited to, software engineering, enterprise, healthcare & life sciences, finance, media & entertainment, consumer agentic assistants Submission period: March 25 — May 13, 2026 (11:59PM Pacific Time) .

Decision letters will be sent out in August 2026. Selected Principal Investigators (PIs) may receive the following: Unrestricted funds, no more than $70,000 USD on average AWS Promotional Credits , no more than $50,000 USD on average Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers Awards are structured as one-time unrestricted gifts.

The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel. Please refer to the ARA program rules on the rules and eligibility page .

Proposals for this CFP should be prepared according to the proposal template and are encouraged to be a maximum of 4 pages, not including Appendices. In addition, to submit a proposal for this CFP, please also include the following information: Please describe how your research differs from or builds upon existing work in your field. What makes your findings, applications, or conceptual framework innovative or unexpected?

Please list the open-source tools you plan to contribute to. Please list the AWS ML tools you will use. ARA will make the funding decisions based on the potential impact to the research community and the quality of the scientific content.

We encourage research that uses machine learning tools, for example AWS AI/ML services (Amazon SageMaker, Amazon AI services, Amazon Bedrock). Expectations from recipients Amazon Research Awards team Applied Scientist - Perception (SLAM/VIO), Fauna We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots.

In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware.

You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments.

The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception.

Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment Sr. Applied Scientist, Special Projects 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 limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology.

Our team rewards 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 forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.

Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers Economist III - AMZ9898444 MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.

COM SERVICES LLC Offered Position: Economist III Job Location: Boston, Massachusetts Job Number: AMZ9898444 Position Responsibilities: Mentor and guide the applied scientists and economists in our organization and hold us to a high standard of technical rigor and excellence in science. Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers.

Work with our engineering partners and draw upon your experience to meet latency and other system constraints. Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. Be responsible for communicating our science innovations to the broader internal & external scientific community.

Position Requirements: Ph. D. or foreign equivalent degree in Economics or a related field and two years of research or work experience in the job offered or a related occupation.

Must have two years of research or work experience in the following skill(s): 1) experience in econometrics including experience with program evaluation, forecasting, time series, panel data, or high dimensional problems; 2) experience with economic theory and quantitative methods; and 3) coding in a scripting language such as R, Python, or similar. 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 $159,200/year to $215,300/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 Principal Applied Scientist, Automated Reasoning Group Applied Scientist, Navigation Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way.

We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments.

At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started.

As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable.

You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees.

Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction.

Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale.

Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines.

We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter. Senior Manager, Applied Science, Prime Video Advertising Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices.

Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+.

All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment and advertising?

Prime Video's technology teams are creating best-in-class digital video experiences, and our Advertising Product & Technology organization is at the forefront of revolutionizing the streaming advertising landscape.

The Prime Video Advertising team delivers ad tech solutions that power Prime Video's rapidly growing advertising business across video-on-demand (VOD), live streaming, and display ads—delivering value to both advertisers and viewers worldwide. We focus on critical areas including ad delivery, machine learning-driven optimization, experimentation, audience measurement, and generative AI-powered ad creative solutions.

We are seeking a Senior Manager, Applied Science to lead a team of scientists and engineers building machine learning and AI solutions that directly impact Prime Video's advertising business.

In this role, you will own the science strategy and execution for key workstreams including: - Ad Load Optimization – Balancing advertising revenue with viewer engagement through sophisticated ML models that determine optimal ad frequency, placement, and duration - Yield Optimization – Maximizing advertising revenue through intelligent allocation, pricing, and forecasting models - Experimentation & Metrics – Designing and scaling experimentation frameworks and causal inference methods to measure the impact of advertising decisions on both business outcomes and customer experience - Ad Creative Generation & Augmentation – Leveraging generative AI to create, personalize, and enhance ad creatives at scale As a leader of leaders, you will set the 3-5 year scientific vision for your organization, build and develop a high-performing team of senior scientists and managers, and drive large-scale ML/AI initiatives that inform strategic decisions for one of the world's largest streaming advertising platforms.

You will collaborate closely with engineering, product, and business teams to translate complex scientific capabilities into measurable business impact during a period of rapid growth with a path to $10B in advertising revenue.

This role offers the unique opportunity to shape the science strategy for a new and fast-growing business, working at the intersection of machine learning, generative AI, causal inference, and advertising technology at Internet scale.

Applied Scientist, AWS Automated Reasoning Sr. Applied Scientist, AWS Automated Reasoning Applied Scientist II, Amazon Fulfillment Technology (AFT) Science The Amazon Fulfillment Technologies (AFT) Science team is seeking an exceptional Applied Scientist with strong operations research and optimization expertise to develop production solutions for one of the most complex systems in the world: Amazon's Fulfillment Network.

At AFT Science, we design, build, and deploy optimization, statistics, machine learning, and GenAI/LLM solutions that power production systems running across Amazon Fulfillment Centers worldwide. We tackle a wide range of challenges throughout the network, including labor planning and staffing, pick scheduling, stow guidance, and capacity risk management.

Our mission is to develop innovative, scalable, and reliable science-driven production solutions that exceed the published state of the art, enabling systems to run optimally and continuously (from every few minutes to every few hours) across our large-scale network.

Key job responsibilities As an Applied Scientist, you will collaborate with scientists, software engineers, product managers, and operations leaders to develop optimization-driven solutions that directly impact process efficiency and associate experience in the fulfillment network.

Your key responsibilities include: - Develop deep understanding and domain knowledge of operational processes, system architecture, and business requirements - Dive deep into data and code to identify opportunities for continuous improvement and disruptive new approaches - Design and develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and emerging challenges - Create prototypes and simulations for agile experimentation of proposed solutions - Advocate for technical solutions with business stakeholders, engineering teams, and senior leadership - Partner with software engineers to integrate prototypes into production systems - Design and execute experiments to test new or incremental solutions launched in production - Build and monitor metrics to track solution performance and business impact About the team Amazon Fulfillment Technology (AFT) designs, develops, and operates end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FCs).

We harmonize the physical and virtual worlds so Amazon customers can get what they want, when they want it. The AFT Science team brings expertise in operations research, optimization, statistics, machine learning, and GenAI/LLM, combined with deep domain knowledge of operational processes within FCs and their unique challenges.

We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment, which includes both developing novel solutions and improving existing approaches. Our production systems rely on a diverse set of technologies, and our teams invest in multiple specialties as the needs of each focus area evolve.

Applied Scientist II, Sponsored Products and Brands-Agent The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon. com and beyond.

We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.

We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

About the team SPB Agent team's vision is to build a highly personalized and context-aware agentic advertiser guidance system that seamlessly integrates Large Language Models (LLMs) with sophisticated tooling, operating across all experiences. The SPB-Agent is the central agent that interfaces with advertisers across Ads Console, Selling Partner portals (Seller Central, KDP, Vendor Central), and internal Sales systems.

We identify high-impact opportunities spanning from strategic product guidance to granular optimization and deliver them through personalized, scalable experiences grounded in state-of-the-art agent architectures, reasoning frameworks, sophisticated tool integration, and model customization approaches including fine-tuning, MCP, and preference optimization.

This presents an exceptional opportunity to shape the future of e-commerce advertising through advanced AI technology at unprecedented scale, creating solutions that directly impact millions of advertisers. Get more from Amazon Science