Description
The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavour.
The Strata team (https://github.com/strata-org) is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span from Infrastructure as Code to high‑performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation.
Key job responsibilities
* Work with customer teams to understand the nature of their software and the properties they need to establish of it.
* Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required.
* Use techniques spanning property‑based testing to model checkers, and interactive theorem provers to establish program properties.
* Explore generative AI techniques to help customers formalise their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs.
About the team
The Agentic Automated Reasoning Group at AWS develops and applies state‑of‑the‑art formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications, with a strong focus on AI‑based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.
Basic Qualifications
* PhD, or a Master's degree and experience in CS, CE, ML or related field research.
* Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
* Experience programming in Java, C++, Python or related language.
* Experience in any of the following areas: algorithms and data structures, parsing, numerical optimisation, data mining, parallel and distributed computing, high‑performance computing.
* Experience in formal verification, program analysis, constraint‑solving, or theorem proving (academic or professional work).
Preferred Qualifications
* Experience with model checking tools and techniques, SAT/SMT solvers.
* Knowledge of one or more methods of defining semantics: operational, denotational, axiomatic, etc.
* Experience applying machine learning and generative AI tools.
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