Applied Scientist, Internal Audit
Core
Build ML and AI solutions, specifically agentic AI systems and generative AI products, to expand self-service data utilization and risk mitigation for Amazon's internal audit teams.
Role type
Senior Applied Scientist (Agentic AI & Generative AI)
Builds
Agentic AI systems, multi-agent workflows, retrieval-augmented generation, and tool-using agents for audit automation.
Domain
Internal Audit, Risk Intelligence, Machine Learning, Generative AI
Deliverable
production ML models | product features
Required skills
Machine Learning fundamentals, Large Language Model architecture and optimization, agentic AI systems design, statistical analysis, SQL, Python, AWS cloud architecture, production ML infrastructure, algorithm design, distributed computing
Preferred skills
Unix/Linux, professional software development, generative AI evaluation frameworks (LLM-as-judge), agentic AI frameworks (LangGraph, Strands), applied research output (publications/talks)
Technologies
AWS (Bedrock, AgentCore, SageMaker), Python, R, Java, C++, LangGraph, Strands
Responsibilities
Design and own agentic AI systems and multi-agent workflows; apply statistical analysis and classical ML to large datasets; architect secure, scalable solutions on AWS ML services; own production and experimentation infrastructure; drive applied research and disseminate findings; mentor junior scientists and engineers.
Seniority
Senior, hands-on IC with mentorship responsibilities