AI Operations Engineer

Bright Vision Technologies • Wildwood, MO

1d • $150,000 - $165,000 • Remote

About The Position

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. The AI Operations Engineer will build and operate large-scale data systems that power AI training and evaluation pipelines. The role combines data engineering expertise with an understanding of AI workloads, focusing on data ingestion, transformation, quality assurance, lineage, and high-throughput delivery to training jobs across diverse modalities. The ideal candidate has operated petabyte-scale data systems, strong software engineering fundamentals, and an understanding of how data infrastructure decisions affect model quality and training efficiency.

This is a full-time, direct W2 position that is 100% remote within the United States. The annual salary range is $150,000–$165,000. Bright Vision Technologies cannot sponsor new H-1B visa petitions for this position; U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are encouraged to apply.

Requirements

• Six or more years of data engineering experience, including significant work supporting ML or AI workloads.
• Strong proficiency in Python and at least one JVM or systems language.
• Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
• Hands-on experience operating petabyte-scale storage and pipeline systems.
• Strong understanding of distributed systems, data modeling, and storage formats.
• Experience with dataset versioning, lineage, and reproducibility for ML workflows.
• Familiarity with high-throughput data loading for accelerator-based training.
• Strong software engineering practices, including testing, CI/CD, and code review.
• Excellent communication and cross-functional collaboration skills.

Nice To Haves

• Experience with multimodal datasets at large scale.
• Familiarity with data quality tooling and dataset evaluation methodology.
• Exposure to privacy-preserving data systems and regulated data handling.
• Open-source contributions to data infrastructure projects.
• Experience supporting frontier model training pipelines.

Responsibilities

• Build and operate large-scale data systems supporting AI training and evaluation pipelines.
• Support data ingestion, transformation, quality assurance, lineage, and high-throughput delivery to training jobs across diverse modalities.
• Operate petabyte-scale storage and data pipeline systems.
• Support ML or AI workloads and account for the effects of data infrastructure choices on model quality and training efficiency.
• Apply software engineering practices including testing, CI/CD, and code review.
• Communicate and collaborate across functions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed