The posting
Applied Scientists on the AWS Vulnerability Management (AVM) Builder Enablement team use program analysis, machine learning and generative AI for managing vulnerabilities and securing the software supply chain across AWS. Our scope covers the third-party open-source packages, language ecosystems, operating systems and kernels that AWS services are built on. Our goal is to take builders out of the remediation loop. When a vulnerability is disclosed or a package is compromised, our systems work out whether it actually affects AWS, generate the fix, check that it's safe and ship it at AWS scale, with one click or no clicks at all.
New vulnerabilities are disclosed every day in the software AWS depends on, and finding and fixing them by hand doesn't scale. We build systems that detect vulnerabilities and work out whether the vulnerable code can actually be reached and exploited in a given service. They rank issues by real risk rather than raw severity scores, then fix them automatically. That can mean upgrading dependencies across ecosystems like Java, Python, JavaScript, Go and Rust, fixing breaking API changes, backporting patches, or patching operating systems and kernels across the fleet. Just as important, we check that each fix is correct and safe, so it can merge with little or no human review.
Beyond known vulnerabilities, we protect the integrity of the software supply chain itself. Modern software is assembled more than it is written, and every dependency is a potential way in for attackers. Securing it means knowing what's in our software, where it came from and whether it can be trusted. Our work here includes building and analyzing software bills of materials (SBOMs), verifying package provenance and build integrity, and detecting malicious or compromised packages before they reach production.
Our methods range from static and dynamic program analysis to LLM-based agents for code repair and upgrades. This is a chance to shape a fast-growing area that directly affects the security of AWS and its customers. You'll apply your technical depth in a fast-moving environment, and your work will reach thousands of AWS builders and services.
Key job responsibilities • Design and build scientific approaches to vulnerability management. This includes vulnerability detection, reachability and exploitability analysis, dependency resolution, and prioritizing risk across third-party packages, operating systems and kernels. • Build program analysis techniques (static analysis, dataflow and call-graph analysis, binary and source analysis) that tell us precisely whether a vulnerability affects a given service or host. • Apply generative AI and agentic coding methods to fix vulnerabilities automatically. Examples include upgrading dependencies, fixing breaking API changes, backporting patches and migrating code across language versions. • Develop ways to check that automated fixes are correct and safe, such as test generation, behavior-equivalence checking, build and runtime checks, and confidence scoring, so changes can merge with little or no human review. • Own the design, experiments and delivery of well-defined science problems from start to finish. Turn ambiguous problems into measurable experiments and deliver solutions with measurable impact, such as faster time to fix, higher fix success rates and fewer false positives. • Work with engineers to turn research prototypes into production systems that run reliably across AWS's codebases and fleet. • Work with security, OS and kernel, and builder-tools partner teams to understand their remediation challenges and data. Find opportunities where science can make a difference. • Stay current with research in software security, program analysis, and ML for code. Contribute to internal and external publications where appropriate. • Share your knowledge through design reviews, documentation and mentoring of junior scientists and engineers.
About the team The AWS Vulnerability Management (AVM) Builder Enablement team protects AWS from security risks in the software it depends on. Our mission is to take builders out of the remediation loop. We find the issues that matter, fix them automatically and ship the fixes safely at AWS scale. Scientists and engineers on the team work side by side, turning research in program analysis and generative AI into production systems that reach thousands of AWS builders.
Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.
Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.
Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
- PhD or equivalent research experience - 3+ years of building models for business application experience - 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 optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux - Experience in professional software development
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Austin - 142,800.00 - 193,200.00 USD annually USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually
