Remote Senior AI Data Engineer — Synthetic Data & Pipelines

Experis; Redmond (WA); Remote; USD 83.000 - 110.000; Vollzeit

Benefits dieser Stelle

Weekly Pay

Medical Plan

Dental Plan

Vision Plan

401(k) Plus Match

Zusammenfassung

Experis is hiring an AI Data Engineer 3 for a remote role based in Redmond, WA. The position focuses on building synthetic data-generation systems and scalable cloud data pipelines, with PST hours and weekly pay.

You will design, implement, and operate data generation workflows in cloud environments, collaborating with AI teams to ensure quality, traceability, and performance across large datasets.

Qualifikationen

• 5+ years of software or data engineering experience or equivalent
• Proficiency in Python, Spring Boot, or .NET
• Strong backend and systems engineering capabilities
• Experience designing and operating data-generation, ETL, and distributed data-processing workflows in cloud pipelines
• Working knowledge of LLMs and AI systems
• Hands-on experience with concurrency, async execution, and event-driven architectures

Aufgaben

• Design, build, and improve synthetic data-generation systems that translate inputs into datasets
• Build and operate scalable pipelines and orchestration with concurrency and asynchronous execution
• Develop data models, storage approaches, and retrieval patterns for large volumes
• Create and evolve validation frameworks with quantitative data quality checks
• Apply cloud engineering practices to deploy, monitor, and support reliable systems

Kenntnisse

5+ years experience

Python

Spring Boot

.NET

Backend engineering

ETL

Cloud data pipelines

LLMs

Asynchronous execution

Jobbeschreibung

Experis is hiring an AI Data Engineer 3 for a remote role based in Redmond, WA. The position focuses on building synthetic data-generation systems and scalable cloud data pipelines, with PST hours and weekly pay.

You will design, implement, and operate data generation workflows in cloud environments, collaborating with AI teams to ensure quality, traceability, and performance across large datasets.