AI Data Engineer: ML Pipelines & RAG Systems

Artifintech; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Artifintech is seeking a Data Engineer in Dallas to design and maintain data infrastructure powering AI/ML initiatives. You will build pipelines for model training, retrieval-augmented generation, and production ML systems, ensuring high-quality data for analytics and AI consumption.

You will collaborate with ML engineers to define data needs, implement data governance, and optimize pipelines for performance and cost. This role blends data engineering with applied AI in a fast-paced environment.

Qualifications

• Experience building data pipelines for AI/ML use cases.
• Knowledge of data governance and lineage.
• Experience with cloud data platforms and unstructured data.

Responsibilities

• Design and build pipelines to ingest, clean, and transform data for AI/ML use cases.
• Build vector embedding pipelines and support vector database integration.
• Develop feature stores/pipelines for ML model training and inference.
• Implement data pipelines supporting RAG architectures with tagging and refresh cycles.
• Partner with ML engineers to capture data requirements for training/evaluation.
• Ensure data lineage, quality, and governance across AI systems.
• Optimize pipelines for cost and performance; enable MLOps workflows.
• Implement entitlement/access control so data access is authorized.

Skills

SQL

Python/Scala

Cloud data platform

Airflow/dbt

Vector embeddings

Unstructured data

Tools

Airflow

dbt

Snowflake Cortex

Job description

Artifintech is seeking a Data Engineer in Dallas to design and maintain data infrastructure powering AI/ML initiatives. You will build pipelines for model training, retrieval-augmented generation, and production ML systems, ensuring high-quality data for analytics and AI consumption.

You will collaborate with ML engineers to define data needs, implement data governance, and optimize pipelines for performance and cost. This role blends data engineering with applied AI in a fast-paced environment.