Senior Data Engineer (GenAI / AWS) | Claude Agent SDK | Amazon Bedrock | Python | 14+ years of experience

Technology Management Solutions LLC; California; Hybrid; USD 150,000 - 210,000; Full time

Job summary

Technology Management Solutions LLC is seeking a Senior Data Engineer to design and deploy large-scale data pipelines on AWS, leveraging GenAI and Claude Agent SDK on Bedrock. You will implement retrieval-augmented generation workflows and maintain vector databases for contextual AI agents.

Ideal candidates have 14+ years in data engineering, deep AWS expertise, and strong Python skills to build scalable, secure data platforms.

Qualifications

• 14+ years of professional experience in data engineering and cloud platforms.
• Strong experience with AWS services for data pipelines.
• Proficiency in Python for data processing and AI workloads.
• Experience with GenAI, RAG workflows, and vector databases.

Responsibilities

• Design and build data pipelines using AWS Step Functions, Lambda, S3, Textract and Comprehend.
• Create document-processing workflows for structured and unstructured data.
• Implement embedding, vector indexing and semantic search.
• Develop and maintain vector databases and knowledge bases for RAG.
• Integrate knowledge bases with AI agents and Claude Agent SDK on Bedrock.
• Build CI/CD pipelines with GitHub Actions for automated builds, tests, deployments.
• Optimize pipelines for scalability, reliability, security, and performance.

Skills

Python

AWS

Data pipelines

GenAI

RAG

CI/CD

Tools

AWS Lambda

S3

Textract

Comprehend

Bedrock

GitHub Actions

Vector DBs

Job description

Senior Data Engineer (GenAI / AWS) | Claude Agent SDK | Amazon Bedrock | Python | 14+ years of experience

• Contract

Duration: 3+ Months (Extension Possible)

Experience: 14+ years Cloud Platform: AWS Primary Language: Python

Key Responsibilities

• 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.

All your information will be kept confidential according to EEO guidelines.