Senior Generative AI Engineer

ZipStaffGlendale, WI
Onsite

About The Position

ZipStaff is seeking a Senior Generative AI Engineer to build production AI for smart-building and industrial-control products at a global building-technology organization. You will ship LLM / GenAI features (operator copilots, alarm analysis, recommendations, NL interfaces) and help the engineering org adopt AI-assisted development. This is a hands-on product + platform seat — not a research-only or prompt-only role.

Requirements

  • 7+ years software engineering with modern development practices.
  • 5+ years hands-on developing and deploying machine learning solutions.
  • Python plus PyTorch, TensorFlow, or Scikit-learn.
  • Experience building and integrating Generative AI / LLM solutions.
  • Familiarity with AWS, Azure, or GCP.
  • Strong software architecture, APIs, data pipelines, and production deployment.
  • Bachelor’s in CS, Software Engineering, Data Science, or related field.
  • Ability to work on-site in Edison, NJ.
  • Must be legally authorized to work in the United States without sponsorship now or in the future.

Nice To Haves

  • RAG , vector databases, and prompt engineering.
  • AI on edge / IoT.
  • MLOps , model monitoring, and AI governance.
  • BAS, industrial controls, IoT, or smart buildings.
  • Agile / Scrum.

Responsibilities

  • Design, build, and deploy AI/ML and GenAI capabilities across cloud, edge, and on-prem.
  • Develop LLM-powered features: operator copilots, intelligent alarm analysis, recommendations, and natural-language interfaces.
  • Integrate AI into existing smart-building products and platforms.
  • Build scalable inference and deployment architectures for production AI.
  • Partner with software engineering and product to turn business needs into AI solutions.
  • Monitor and improve model performance, reliability, and accuracy.
  • Introduce AI-assisted developer tools that improve delivery velocity.
  • Use AI for code generation, testing, reviews, and CI/CD.
  • Set AI engineering standards and governance.
  • Mentor engineers on AI frameworks and implementation.
  • Evaluate emerging tools and drive responsible AI use across the SDLC.
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