Applied Scientist, AVM Builder Enablement

Amazon is hiring an Applied Scientist, AVM Builder Enablement in Arlington, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Level.

AI in this role

Design and build ML and LLM-based systems for automated vulnerability detection, code repair, and software supply chain security.

pythonjavarustgollm-agents

machine-learningprogram-analysissoftware-supply-chainvulnerability-management

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.

Basic qualifications

- 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

Preferred qualifications

- 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

How we rate this

Applied Scientist, AVM Builder Enablement at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Applied Scientist, AVM Builder Enablement is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $143k-$193k a year.
The role is based in US, VA, Arlington.
The job was posted on October 14, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningProgram AnalysisSoftware Supply ChainVulnerability ManagementPythonJavaRustGo

Also common in applied scientist jobs at this level

Deep learning NLP TensorFlow Spark Reinforcement learning Computer vision

Pay

This job starts at: $143k
Typical applied scientist job: $167k

This posting starts 15% below the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where program analysis was part of your work. What did you do?
Tell me about a project where software supply chain was part of your work. What did you do?
Tell me about a project where vulnerability management was part of your work. What did you do?
Walk me through how you've used Python in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Machine learning, Program Analysis, Software Supply Chain, Vulnerability Management, and Python. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.

Get a free CV review Check your resume with the ATS resume checker

Get new applied scientist jobs (Builds AI ●●●●) by email

One email a week with the new applied scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.