Senior Data Engineer: GenAI & AWS | Remote/Hybrid Travel

Simple Solutions

Jacksonville (FL)

Hybrid

USD 96,000 - 131,000

Full time

2 days ago
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Job summary

Simple Solutions seeks a Sr. Data Engineer (GenAI & AWS) to design and build scalable data pipelines in AWS, focusing on Retrieval-Augmented Generation and AI agent integration. Remote/hybrid with travel to client sites, time-zone coverage broadens the candidate pool across US West Coast.

Requires 12–20+ years, Python and cloud expertise. Key responsibilities include building pipelines with Lambda/S3, embedding/vector search, CI/CD with GitHub Actions, and deploying agents on Bedrock.

Qualifications

  • Must have 12–20+ years of data/engineering experience.
  • Experience with GenAI architectures and AWS cloud.
  • Ability to design scalable data pipelines and AI-enabled workflows.

Responsibilities

  • Design and develop data pipelines using AWS services.
  • Build automated document-processing workflows with AI components.
  • Implement vector search, embeddings, and RAG for knowledge retrieval.
  • Develop and maintain AI agents with Bedrock and Claude SDKs.
  • Create CI/CD pipelines with GitHub Actions and IaC with Terraform/AWS CDK.
  • Optimize pipelines for scalability, security, and performance.

Skills

Python
SQL
TypeScript
AWS Step Functions
AWS Lambda
AWS S3
Amazon Textract
Amazon Comprehend
Document AI / OCR
Vector databases
Embeddings
RAG
Knowledge-base integration
Claude Agent SDK
Amazon Bedrock
GitHub Actions CI/CD
Terraform
AWS CDK
AWS IAM
API integrations
AgentCore Runtime

Tools

(none)

Job description

Simple Solutions seeks a Sr. Data Engineer (GenAI & AWS) to design and build scalable data pipelines in AWS, focusing on Retrieval-Augmented Generation and AI agent integration. Remote/hybrid with travel to client sites, time-zone coverage broadens the candidate pool across US West Coast.

Requires 12–20+ years, Python and cloud expertise. Key responsibilities include building pipelines with Lambda/S3, embedding/vector search, CI/CD with GitHub Actions, and deploying agents on Bedrock.

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