Senior GenAI Data Scientist — Enterprise AI & Agents

Amazon Web Services (AWS); Arlington (VA); On-site; USD 159,000 - 215,000; Full time

Benefits offered by this job

Health benefits

RSUs and comprehensive benefits

Job summary

Amazon Web Services, Inc. is seeking a Senior Generative AI Data Scientist to lead enterprise GenAI initiatives in NAMER, translating complex business problems into data-driven GenAI and ML solutions using AWS Bedrock and related services.

You will architect, deploy, and validate LLM-powered agents and workflows, collaborating with executives, product leaders, and data science teams to accelerate cloud adoption and provide strategic guidance on best practices in AI safety, governance, and ROI.

Qualifications

• 5+ years of data querying languages (SQL), scripting (Python), or statistical software (R/SAS/Matlab) experience.
• 4+ years of data scientist experience.
• Experience with statistical models e.g. multinomial logistic regression.
• Master's degree or higher in a quantitative field (stats, CS, data science).
• 5+ years of end-to-end architecture, design, deployment for GenAI/ML platforms.

Responsibilities

• Translate customer business challenges into data-science driven GenAI solutions using AWS.
• Define, design and deploy ML models, agentic workflows and GenAI apps for enterprise customers.
• Engage with senior engineers, data scientists, and executives to guide adoption patterns and best practices.

Skills

SQL

Python

Statistical modeling

LLM architectures

End-to-end ML/GenAI

Executive engagement

Education

Master's degree or higher in statistics / data science / CS

Tools

SageMaker

Bedrock

AgentCore

LangChain

LangGraph

CrewAI

Kubernetes

Docker

Job description

Amazon Web Services, Inc. is seeking a Senior Generative AI Data Scientist to lead enterprise GenAI initiatives in NAMER, translating complex business problems into data-driven GenAI and ML solutions using AWS Bedrock and related services.

You will architect, deploy, and validate LLM-powered agents and workflows, collaborating with executives, product leaders, and data science teams to accelerate cloud adoption and provide strategic guidance on best practices in AI safety, governance, and ROI.