Applied Scientist II, AWS Security

Amazon Web Services, Inc. is seeking an Applied Scientist to improve the security of open source software and the broader software supply chain. The role focuses on designing, building, and operating AI-powered security solutions, developing machine learning models, automating security workflows, and translating scientific research into scalable production systems.

Responsibilities:

• Architect and build AI-powered security applications and tooling — Design and implement LLM-based systems (leveraging Bedrock, SageMaker, and state of the art patterns) for intelligent code scanning, automated solution development/deployment, and remediation alternatives
• Transform manual processes – Reimagine and deliver change from low throughput, human-dependent processes into high volume, machine speed pipelines without sacrificing key quality metrics
• Collaborate with and influence other leaders – The open source ecosystem has many stakeholders, and change requires listening and supporting but also influencing and leading through action
• Drive proactive security automation — Build systems that identify and remediate security issues in deliverables (code, threat models, content) without requiring explicit builder consent at every step, moving from reactive reviews to proactive prevention
• Own operational excellence — Define and maintain SLAs, monitoring, alerting, runbooks, and incident response for services you own; participate in on-call rotation to support 24/7 availability
• Lead technical design — Produce design documents, conduct trade-off analysis, and drive alignment across organizations
• Design and conduct scientific research using machine learning and deep learning techniques to address complex, ambiguous problems, working backwards from customer needs to invent new approaches or extend existing ones
• Build, train, and evaluate production-quality models using frameworks such as PyTorch or TensorFlow, applying rigorous experimentation, feature engineering, and hyperparameter optimization to improve accuracy and performance
• Write clean, maintainable code with optimal data structures and algorithms, ensuring your components integrate directly into production systems and meet high standards for operational reliability and resource efficiency
• Collaborate with engineering and product partners to translate scientific insights into scalable solutions, clearly communicating design decisions and trade-offs to ensure long-term maintainability
• Contribute to the scientific community by authoring or co-authoring peer-reviewed publications, mentoring less experienced scientists, and participating in technical reviews across teams