Mid - Senior AI Engineer - QE

Mid-Senior AI Engineer - QE Skilled
Seeking a hybrid role in Chicago 2 days/week
Expected Employment Duration - 6 months +

Technical Domains of Mastery

The resource must demonstrate hands-on capability across three core pillars, complemented by a strong QA/QE pedigree:

• The MERN Stack & Full SDLC: Active, full-lifecycle application development using MongoDB, Express, React, and Node.js (or TypeScript/JavaScript variants), backed by 5+ years of deep familiarity with enterprise dev tools (Docker, Git, VS Code, npm/pip).
• Vertex AI & RAG Architecture: Demonstrated experience building AI capabilities, engineering agent behaviors, and defining pipelines specifically within the Google Cloud (Google Cloud Platform) Vertex AI ecosystem. Experience with equivalent AI services on other major cloud platforms (AWS, Azure) is an acceptable alternative.
• QE Pedigree: Demonstrable experience in an active QE role with a deep, foundational understanding of modern QE concepts, automation practices, and testing methodologies is highl valued. Prior experience with automation tools like Playwright or  is a plus.