AmazonApplied Scientist, Internal Audit
Amazon is hiring an Applied Scientist, Internal Audit in Arlington, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions LangGraph, Bedrock and SageMaker among its tools and skills.
- Level classes it as a senior role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Design and build agentic AI systems, machine learning models, and generative AI products to automate and augment internal audit work.
Key job responsibilities
- Partner with audit teams, product managers, engineers, and scientists to define and deliver machine learning and generative AI products that carry significant ambiguity, scale, and complexity, owning problems end-to-end, from framing through measurable impact.
- Design, build, and own agentic AI systems, including multi-agent workflows, retrieval-augmented generation, and tool-using agents, that automate and augment audit work, and set the standard for how the team evaluates them through rigorous LLM-as-judge and human-aligned evaluation.
- Apply statistical analysis and classical machine learning using SQL and scripting languages like Python/R over large datasets to develop insights and recommendations that strengthen internal audit.
- Architect secure, scalable solutions on AWS machine learning and generative AI services (e.g., Bedrock, AgentCore, SageMaker), owning the full lifecycle from design through production deployment, monitoring, and iterative improvement.
- Own and evolve the team's production and experimentation infrastructure, including deployment pipelines, observability and tracing, and evaluation harnesses.
- Drive applied research by identifying and pursuing emerging techniques, and disseminate findings through internal and external publications, talks, and journal clubs.
- Raise the technical bar across the team, including mentor junior scientists and engineers, review designs and code, and help shape the product and technical roadmap.
A day in the life
As an Applied Scientist, you will own ambiguous, high-impact problems and help shape the technical roadmap that connects risk to Amazon. You will drive AI products that make audit work more effective and efficient, increasingly centered on LLM and agentic systems. You set technical direction across the full arc of applied science. That means framing problems, making architecture decisions, defining how the team evaluates quality, and delivering solutions in production. The ideal candidate pairs deep machine learning expertise with a builder's instinct for production architecture. They thrive on ambiguity, mentor others, and follow a fast-moving research frontier.
About the team
Internal Audit’s mission is to help our businesses improve controllership, operational efficiency, and customer experience.
Basic qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 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 with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience building complex software systems that have been successfully delivered to customers
- Experience architecting/operating solutions built on AWS, or experience implementing a cloud-based technology solution
Preferred qualifications
- Experience using Unix/Linux
- Experience in professional software development
- Experience designing and running evaluation frameworks for generative AI (e.g., LLM-as-judge, human-alignment measurement, benchmarking output quality).
- Hands-on experience with agentic AI frameworks and generative AI services (e.g., Amazon Bedrock, SageMaker, LangGraph, Strands).
- Experience building and maintaining production ML/AI infrastructure — deployment pipelines, observability/tracing, and experimentation environments.
- A track record of applied-research output: publications, conference talks, or patents.
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, VA, Arlington - 142,800.00 - 193,200.00 USD annually
How we rate this
Applied Scientist, Internal Audit at Amazon rates 90 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.
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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
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
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where generative ai was part of your work. What did you do?
- Tell me about a project where agentic ai was part of your work. What did you do?
- Tell me about a project where statistical analysis was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, Machine learning, Generative AI, Agentic AI, and Statistical Analysis. 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.
Get your CV reviewed before you apply
Send your CV and the role you want next. Your review arrives by email within 3 days.
Get new applied scientist jobs (Builds AI ●●●●) by email
One email a week, each job rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free.
Similar roles
Research roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step