Job Description Role: Senior Data Engineer (GenAI / AWS) Duration: 3+ Months (Extension Possible) Location: Los Angeles, CA (Remote/Hybrid) Employment Type: C2C Experience: 14+ Years Note: AWS certification is required. We are looking for a highly experienced Senior Data Engineer with strong expertise in AWS, Python, Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will design and build scalable AI-powered document processing solutions, vector search pipelines, and intelligent AI agents on AWS. Key Responsibilities Design and develop scalable data pipelines using AWS Step Functions, Lambda, S3, Textract, and Comprehend. Build automated document-processing workflows for structured and unstructured data. Implement document chunking, embeddings, vector indexing, semantic search, and RAG solutions. Develop and maintain vector databases and knowledge bases. Integrate knowledge bases with AI agents for contextual information retrieval. Build and deploy AI agents using Claude Agent SDK on Amazon Bedrock AgentCore Runtime. Develop and maintain CI/CD pipelines using GitHub Actions. Optimize data pipelines for scalability, security, reliability, and performance. Must-Have Skills 14+ years of Data Engineering experience. Python, SQL AWS Step Functions, Lambda, S3 Amazon Textract and Comprehend Document AI / OCR Vector databases and embeddings Document chunking and indexing Advanced retrieval and reranking RAG and knowledge-base integration Amazon Bedrock Claude Agent SDK AgentCore Runtime GitHub Actions CI/CD AWS IAM and API integrations Good-to-Have Skills TypeScript AWS Glue OpenSearch, Pinecone, pgvector LangChain / LlamaIndex Terraform / AWS CDK Additional Information All your information will be kept confidential according to EEO guidelines.
Summary
Design and build scalable AI-powered document processing, vector search, and RAG pipelines on AWS using Python, Amazon Bedrock, and Claude Agent SDK. Requires 14+ years of data engineering experience, AWS certification, and expertise in Step Functions, Lambda, S3, Textract, and Comprehend.
Responsibilities
Design and develop scalable data pipelines using AWS Step Functions, Lambda, S3, Textract, and Comprehend; build automated document-processing workflows; implement document chunking, embeddings, vector indexing, semantic search, and RAG solutions; develop and maintain vector databases and knowledge bases; integrate knowledge bases with AI agents; build and deploy AI agents using Claude Agent SDK on Amazon Bedrock AgentCore Runtime; develop and maintain CI/CD pipelines using GitHub Actions; optimize data pipelines for scalability, security, reliability, and performance.
Qualifications
14+ years of Data Engineering experience; AWS certification is required.
Experience requirements
14+ years of Data Engineering experience.