Why This Role Stands Out
This hybrid AI Data Engineer role offers significant career growth through hands-on experience with cutting-edge Generative AI and LLM technologies, allowing you to make a substantial impact on client success. You'll thrive here if you possess strong Python, SQL, and cloud platform skills, coupled with a passion for building robust data pipelines for AI applications. Embrace this exciting opportunity to advance your career in a dynamic tech environment.
Quick Overview
Job Description
We at NJ TECH INC are focused on hiring highly skilled professionals who are excited by the opportunity to make a true impact on their careers as well as on our clients' business. We power our clients success - and drive our consultants career growth.
We are seeking an experienced and outstanding AI Data Engineer for one of our esteemed clients.
Role: AI Data Engineer
Location: Charlotte NC
Duration : Long term
Required Skills
- Strong experience in Data Engineering with hands-on Python development.
- Strong SQL skills with experience in data modeling, data transformation, and data quality.
- Experience building and maintaining ETL/ELT data pipelines.
- Hands-on experience with Generative AI, LLMs, RAG, and AI/ML applications.
- Experience working with OpenAI, Azure OpenAI, or other LLM platforms.
- Experience with prompt engineering, embeddings, vector databases, and retrieval-augmented generation (RAG).
- Experience integrating AI/LLM services with data platforms and enterprise applications.
- Strong experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
AI/GenAI Responsibilities
- Design and develop data pipelines that support AI/ML and Generative AI applications.
- Prepare and transform structured and unstructured data for LLM and AI use cases.
- Build data ingestion pipelines for RAG and LLM applications.
- Develop workflows for document processing, chunking, metadata extraction, embeddings, and vector search.
- Integrate LLMs, vector databases, and enterprise data sources.
REGARDS
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