AI Data Engineer: Scalable Pipelines & Vector AI

Artifintech; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Artifintech, based in Atlanta, seeks an experienced AI Data Engineer to design, build, and scale data pipelines for AI/ML initiatives. You will work with SQL and Python/Scala, leverage cloud data platforms, and develop vector embedding pipelines and RAG workflows to support model training and inference.

Collaborate with ML Engineers and Data Scientists to ensure data quality, governance, and secure access across pipelines, while optimizing performance and cost.

Qualifications

• Proficient in SQL and Python/Scala for building data pipelines.
• Experience with cloud data platforms.
• Hands-on with Apache Airflow and dbt.
• Knowledge of embedding models, vector search, and RAG architectures.
• Experience processing structured and unstructured data.
• Understanding of ML lifecycle concepts and data engineering best practices.

Responsibilities

• Design and develop data pipelines to ingest, clean, and transform data.
• Build and maintain vector embedding pipelines and integrate vector databases.
• Develop data pipelines and feature stores for ML model training and inference.
• Implement RAG pipelines, including document chunking, embedding refresh, and metadata tagging.
• Collaborate with ML Engineers and Data Scientists to support model training and evaluation.
• Ensure data quality, lineage, governance, and security across AI data pipelines.
• Optimize data pipelines for performance, scalability, and cost efficiency.
• Support MLOps/LLMOps workflows, including dataset versioning and reproducibility.
• Implement data access controls and entitlement logic to ensure secure AI data usage.

Skills

SQL

Python/Scala

Cloud data platforms

Vector embeddings

RAG architectures

Structured/unstructured data

Data governance

Data quality

Tools

Apache Airflow

dbt

Job description

Artifintech, based in Atlanta, seeks an experienced AI Data Engineer to design, build, and scale data pipelines for AI/ML initiatives. You will work with SQL and Python/Scala, leverage cloud data platforms, and develop vector embedding pipelines and RAG workflows to support model training and inference.

Collaborate with ML Engineers and Data Scientists to ensure data quality, governance, and secure access across pipelines, while optimizing performance and cost.