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# Sr. Data Engineer (GenAI & AWS) Remote/Hybrid with Travel

- **Company:** Simple Solutions
- **Location:** Jacksonville, FL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Continuous Integration, Github, Identity and Access Management, Information Retrieval, Python (Programming Language), Search Technologies, SQL Databases, TypeScript, Unstructured Data, AWS Cdk, Pinecone, Retrieval-Augmented Generation, Llamaindex, AgentCore, Generative AI, Indexer, Agentic-AI, Build Management, Pgvector, Amazon Bedrock, AWS Glue, Claude, Terraform, Agent SDK, Intelligent Document Processing, Data Pipelines, Api Management, OpenSearch
- **Published:** October 27, 2026
- **Apply:** https://www.thejobnetwork.com/job/d1ba4477-eb32-440c-be54-5d3a1d950c00/sr-data-engineer-genai-aws-remotehybrid-with-travel

## About the Role

The key is time zone coverage and so we can expand our search across the West Coast - remote/hybrid but necessarily located in the western time zones. You must be comfortable to travel to the client site for workshops/meetings., Python, SQL

TypeScript

AWS Step Functions, Lambda, S3

AWS Glue

Amazon Textract and Comprehend

Document AI / OCR

Vector databases and embeddings

OpenSearch, Pinecone, pgvector

Document chunking and indexing

Advanced retrieval and reranking

RAG and knowledge-base integration

LangChain / LlamaIndex

Amazon Bedrock

Claude Agent SDK

GitHub Actions CI/CD

Terraform / AWS CDK

AWS IAM and API integrations

AgentCore Runtime

Important: If this individual must personally build and deploy the Claude agents, move Claude Agent SDK and AgentCore Runtime into the must-have category.

## Description

Overall experience: 12-20+ years Cloud Platform: AWS Primary Language: Python, * Design and develop data pipelines using AWS Step Functions, Lambda, S3, Textract, and Comprehend.

 * Build automated document-processing workflows for extracting, transforming, and processing structured and unstructured data.
 * Implement document chunking, embeddings, vector indexing, and semantic search.
 * Develop and maintain vector databases and knowledge bases to support Retrieval-Augmented Generation (RAG).
 * Integrate knowledge bases with AI agents for contextual information retrieval.
 * Build AI agents using Claude Agent SDK and deploy them on Amazon Bedrock AgentCore Runtime.
 * Develop CI/CD pipelines using GitHub Actions to automate builds, testing, and deployments.
 * Optimize data pipelines for scalability, reliability, security, and performance.