AI Data Engineer

Role: AI Data Engineer

Location: Tennessee, remote-OK

Contract

Mandatory Skills- Python, AI/ML

Retail domain experience is highly preferable.

JD:

We are seeking an experienced AI Data Engineer (15+ Years) to design, develop, and manage scalable data platforms that enable advanced analytics, Machine Learning (ML), and Generative AI solutions. The ideal candidate will build robust data pipelines, ensure data quality, and integrate AI/ML capabilities into enterprise data ecosystems.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.

Build and optimize data lakes, data warehouses, and AI-ready data platforms.

Develop ingestion, transformation, and orchestration frameworks using cloud-native technologies.

Prepare, cleanse, and engineer datasets for AI/ML and Generative AI workloads.

Integrate Large Language Models (LLMs), vector databases, embeddings, and RAG (Retrieval-Augmented Generation) pipelines into enterprise solutions.

Implement data governance, security, lineage, and quality controls.

Collaborate with Data Scientists, AI Engineers, Business Analysts, and Solution Architects.

Monitor, troubleshoot, and optimize data pipelines and platform performance.

Automate deployment, testing, and monitoring of data engineering workflows.

Create technical documentation and data dictionaries for enterprise data assets.

Required Skills

Technical Skills

Python, SQL, PySpark

ETL/ELT development

Data Modeling (Star Schema, Snowflake Schema)

Apache Spark, Databricks

Airflow, Dataflow, Informatica, ADF, Synapse, or equivalent tools

Relational & NoSQL Databases

Data Warehousing concepts

REST APIs and Microservices

Git, CI/CD, DevOps practices

AI & GenAI Skills

Machine Learning fundamentals

Data preparation for AI models

Vector Databases (Pinecone, ChromaDB, FAISS)

LLM Integration (OpenAI, Azure OpenAI, Gemini, Claude, etc.)

RAG Architecture

Embeddings and Semantic Search

Prompt Engineering fundamentals