The Automated Reasoning Group is looking for an Applied Scientist with experience in building scalable formal reasoning solutions that delight customers. You will be part of a world-class team building the next generation of tools and services by combining Automated Reasoning and Generative AI.

AWS has the most services and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things.

You will apply your knowledge to propose solutions, create software prototypes, and move prototypes into production systems using modern software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You will use your strong verbal and written communication skills, are self-driven and own the delivery of high quality results in a fast-paced environment.

Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. See https://aws.amazon.com/security/provable-security/

As an Applied Scientist in AWS AI, you will play a pivotal role in shaping the definition, vision, design, roadmap and development of product features from beginning to end. You will:

* Define and implement new formal reasoning applications that employ scalable and efficient approaches to solve complex problems using Automated Reasoning and Generative AI technologies.
* Apply software engineering best practices to ensure a high standard of quality for all team deliverables
* Work in an agile, startup-like development environment, where you are always working on the most important stuff
* Deliver high-quality scientific artifacts
* Work with the team to lower the barrier of adoption for interactive theorem provers
* Work with the team to help drive business decisions

Learn and Be Curious. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.

Inclusion and Diversity. Our team is diverse! We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, Amazon Women and Engineering, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more.

Key job responsibilities
* Design and implement scalable systems for formal reasoning and automated theorem proving.
* Collaborate closely with internal and external users to understand their requirements for formal verification and automated reasoning.
* Enhance and extend the capabilities of formal reasoning systems to meet application-specific demands.
* Proactively identify and explore new opportunities for deploying and leveraging formal reasoning solutions across various domains.

About the team
The AWS Automated Reasoning Group is a talented group of scientists from around the world. Their areas of expertise include interactive theorem proving, generative AI, SAT/SMT solvers, and programming language theory.