Applied Scientist: Agentic AI for Audit Intelligence

Amazon Science; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon is seeking an Applied Scientist to accelerate Amazon Internal Audit’s Data Science & Risk Intelligence initiatives. You will design, build, and deploy ML and agentic AI solutions to surface insights and mitigate risk within a fast-paced environment.

The role involves collaborating with audit teams, product managers, and engineers, and working with AWS services such as SageMaker and Bedrock. A strong emphasis on multi-agent workflows and rigorous evaluation is required.

Qualifications

• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field.
• Experience programming in Java, C++, Python or related language
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
• Experience researching about machine learning, deep learning, NLP, computer vision, data science
• Experience building applications with large language models (e.g., prompt engineering, retrieval-augmented generation, or agentic/tool-using workflows)

Responsibilities

• Work with audit teams, product managers, engineers, and more senior scientists to deliver machine learning and generative AI products that carry real degrees of ambiguity, scale, and complexity.
• Design, build, and evaluate agentic AI systems — multi-agent workflows, retrieval-augmented generation, and tool-using agents — that automate and augment audit work, applying rigorous LLM-as-judge and human-aligned evaluation to measure and improve output quality.
• 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 prototype through production deployment, monitoring, and iterative improvement, working closely with auditors to understand their business needs.
• Build and maintain the team's production and experimentation infrastructure, including deployment pipelines, observability and tracing, and evaluation harnesses.
• Advance applied research by exploring emerging techniques and sharing findings through internal and external publications, talks, and conferences.

Skills

Machine learning

Data analysis

Statistics

NLP

Deep learning

Education

Master's degree in computer science / mathematics / statistics / ML

PhD in Engineering / Computer Science / ML / ORS / Statistics (or related)

Tools

SQL

RDBMS

Data Warehouse

Python

Java/C++

Job description

Amazon is seeking an Applied Scientist to accelerate Amazon Internal Audit’s Data Science & Risk Intelligence initiatives. You will design, build, and deploy ML and agentic AI solutions to surface insights and mitigate risk within a fast-paced environment.

The role involves collaborating with audit teams, product managers, and engineers, and working with AWS services such as SageMaker and Bedrock. A strong emphasis on multi-agent workflows and rigorous evaluation is required.