Senior GenAI Data Scientist — AI Agents & Bedrock Lead

Amazon; Carlisle (Cumberland County); Hybride; USD 180 000 - 280 000; Plein temps

Avantages offerts par ce poste

Health insurance

401(k) matching

RSUs included

Résumé du poste

Amazon is seeking a Senior GenAI Data Scientist to design and deploy Generative AI solutions for NAMER enterprise customers, translating business challenges into data‑driven, production‑ready systems on AWS.

You will engage with senior engineers, data scientists, and executives to influence architectural trade‑offs, architect agentic workflows, and evaluate LLM-powered applications leveraging Bedrock, SageMaker, and open‑source tooling.

Qualifications

• 5+ years of data querying languages (SQL), scripting (Python) or stats software (R/SAS/Matlab)
• 4+ years of data scientist experience
• Master's degree or higher in a quantitative field
• 5+ years in end-to-end technical architecture, design, deployment for Generative AI/ML
• 3+ years with LLM tech including architectures and evaluation

Responsabilités

• Work with NAMER Enterprise customers to design and implement GenAI solutions using AWS services (Bedrock, SageMaker).
• Build prototypes, PoCs, and evaluate AI solutions with customers.
• Lead discussions with senior leaders to influence technical decisions and product feedback.
• Develop and support GenAI agentic workflows and tools using open frameworks.

Connaissances

SQL

Python

R/SAS/Matlab

Statistical Modeling

End-to-end ML/GenAI

Formation

Master's degree or higher in quantitative field

Outils

Kubernetes

Docker

LangChain

LlamaIndex

LangGraph

CrewAI

SageMaker

Step Functions

OpenSearch

PgVector

S3

IAM

Description du poste

Amazon is seeking a Senior GenAI Data Scientist to design and deploy Generative AI solutions for NAMER enterprise customers, translating business challenges into data‑driven, production‑ready systems on AWS.

You will engage with senior engineers, data scientists, and executives to influence architectural trade‑offs, architect agentic workflows, and evaluate LLM-powered applications leveraging Bedrock, SageMaker, and open‑source tooling.