Senior GenAI Data Scientist — AI Agents & Bedrock Lead

Amazon

Carlisle (Cumberland County)

Hybrid

USD 180,000 - 280,000

Full time

6 days ago
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Benefits offered by this job

Health insurance
401(k) matching
RSUs included

Job summary

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

Responsibilities

  • 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.

Skills

SQL
Python
R/SAS/Matlab
Statistical Modeling
End-to-end ML/GenAI

Education

Master's degree or higher in quantitative field

Tools

Kubernetes
Docker
LangChain
LlamaIndex
LangGraph
CrewAI
SageMaker
Step Functions
OpenSearch
PgVector
S3
IAM

Job description

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.

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