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Description

Are you passionate about data, enjoy solving complex analytical problems, leveraging industry leading agentic AI technologies to derive insight at scale - all in a challenging, fast-paced environment? We are seeking an Applied Scientist to accelerate the growth of Amazon Internal Audit’s Data Science & Risk Intelligence initiatives. The team builds ML and AI solutions that expand self-service data utilization by audit teams, utilizing the right methods to derive deeper patterns, and surface insights to gain holistic perspectives while amplifying potential risk mitigation.

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.