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Applied Scientist, AI Security

Amazon.com Inc
  • Austin, TX
    17 days ago

    Job Description

    We are seeking an Applied Scientist to join our AI Security team, which builds AI-based security analysis services that identify, validate, and help remediate vulnerabilities in Amazon source code and cloud configurations. The team combines large language models, security knowledge, code analysis, and security-engineer feedback to help builder teams detect security issues earlier in development and maintain security coverage across Amazon.

    As an Applied Scientist, you will research, model, design, and implement machine learning and agentic systems that reason over source code, infrastructure, and security context. You will collaborate with applied scientists, security engineers, software engineers, internal partners, and external researchers to improve finding precision, severity assessment, remediation quality, and continuous scanning coverage. Your work will enable continuous, AI-driven security analysis across Amazon's software estate, converting source-code and infrastructure signals into validated, prioritized findings and proposed fixes that help builders prevent security defects from reaching production.

    Key job responsibilities

    • Research and develop accurate and scalable methods to solve our hardest AI security problems
    • Lead cross-functional work with applied scientists, software engineers, and security engineers to develop models and technical designs for AI systems that analyze source code, validate security findings, and generate remediation guidance at Amazon scale.

    About the team

    As an Applied Scientist on the AI Security team, you will research, develop, evaluate, and productionize models that identify security vulnerabilities in source code and cloud configurations. You will design experiments, build evaluation datasets and metrics, and apply large language models, program analysis, and security knowledge to improve finding precision, severity assessment, and remediation quality. You will work with applied scientists, security engineers, and software engineers to deliver systems that convert security signals into validated, prioritized findings and proposed fixes for builder teams across Amazon.

    Your work will shape how Amazon identifies and addresses security defects throughout the software development lifecycle. You will investigate model behavior, analyze failure modes, develop methods to improve recall and precision, and measure the impact of new capabilities before deployment. The role provides opportunities to solve applied machine learning problems across source code, infrastructure, cloud services, and security operations.

    About the team

    The AI Security team develops systems that analyze source code and cloud configurations to identify, validate, and help remediate security vulnerabilities. We combine large language models, security engineering, automated evaluation, and feedback from builders and security engineers to improve security coverage across Amazon. The team works on problems including vulnerability detection, severity assessment, false-positive reduction, remediation generation, continuous scanning, and security-data analysis.

    Diverse Experiences

    Amazon Security values varied professional and life experiences. We encourage candidates from traditional and nontraditional career paths, including candidates early in their careers and candidates with alternative technical backgrounds, to apply.

    Why Amazon Security?

    Security is central to customer trust and Amazon's products and services. Our organization establishes and maintains security standards across Amazon. Team members build experience across cloud, devices, retail, entertainment, healthcare, operations, and physical stores.

    Inclusive Team Culture

    Amazon Security brings together people with different experiences, technical backgrounds, and perspectives. We invest in learning opportunities and create space for teams to examine security problems from multiple viewpoints.

    Training and Career Growth

    The team provides knowledge-sharing, technical training, mentorship, and opportunities to work across security domains. Applied Scientists can deepen their expertise in machine learning, security research, evaluation systems, and production AI services.

    Work/Life Balance

    We support work-life harmony and flexible working practices. Teams plan work with sustainable delivery in mind and support employees in meeting responsibilities at work and at home.

    Numbers & Facts

    LocationAustin, TX
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

    Skills

    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Bug Tracking Softwareunmatched
    • Cloud Computingunmatched
    • Computer Securityunmatched
    • Cross-Functionalunmatched
    • Data Analysisunmatched
    • Establish Prioritiesunmatched
    • Experiment Designunmatched
    • Failure Analysisunmatched
    • Healthcareunmatched
    • Infrastructure as a Service (IaaS)unmatched
    • Knowledge Modelingunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Metricsunmatched
    • Modeling Languagesunmatched
    • Protective Servicesunmatched
    • Research & Development (R&D)unmatched
    • Retailunmatched
    • Scalable System Developmentunmatched
    • Security Analysisunmatched
    • Security Softwareunmatched
    • Software Development Lifecycle (SDLC)unmatched
    • Software Engineeringunmatched
    • Systems Analysisunmatched
    • Systems Engineeringunmatched
    • Technical/Engineering Designunmatched
    • Training Data Setsunmatched

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