AI Data Engineer: Pipelines, Vectors & MLOps

gobravvo; Phoenix (AZ); On-site; USD 110,000 - 160,000; Full time

Job summary

gobravvo is seeking a Data Engineer to build and maintain data infrastructure for AI and ML initiatives. You will design robust pipelines for both structured and unstructured data, enabling analytics and AI model access.

You will work with vector embeddings, feature stores, and RAG architectures, ensuring data lineage, quality, and governance across pipelines. Prior experience with cloud platforms and MLOps is essential.

Qualifications

• Proficiency in SQL and at least one programming language (Python or Scala) for pipeline development.
• Experience with cloud data platforms and data orchestration tools.
• Knowledge of ML lifecycle and MLOps practices.

Responsibilities

• Design and implement data pipelines to ingest, clean, and transform data from various sources.
• Develop and maintain vector embedding pipelines and support vector database integration.
• Create feature stores and pipelines for model training and inference.
• Implement data pipelines for RAG architectures, including chunking strategies and metadata tagging.
• Collaborate with ML engineers and data scientists to align data infrastructure with model requirements.

Skills

SQL

Python

Scala

Tools

Airflow

dbt

Snowflake

AWS

Job description

gobravvo is seeking a Data Engineer to build and maintain data infrastructure for AI and ML initiatives. You will design robust pipelines for both structured and unstructured data, enabling analytics and AI model access.

You will work with vector embeddings, feature stores, and RAG architectures, ensuring data lineage, quality, and governance across pipelines. Prior experience with cloud platforms and MLOps is essential.