Lead GenAI Engineer - GCP & Vertex AI Expert

Quantum Technologies. LLC

Minneapolis (MN)

On-site

USD 77,000 - 110,000

Full time

3 hours ago
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Job summary

Quantum Technologies LLC is seeking a Lead Software Engineer focused on GenAI/GCP in Minneapolis, MN for an initial 6-month engagement with extension possible. The role offers a flexible, high-impact environment with a bill rate of $68/hour and multiple work arrangements (W-2, 1099, C2C).

The candidate will lead design and implementation of enterprise-grade GenAI solutions, build RAG apps, fine-tune LLMs, and deploy AI workloads on cloud platforms, using Python, FastAPI/Flask, and containerized

Qualifications

  • Hands-on experience with Python and AI frameworks.
  • Experience with LLM fine-tuning and deployment.
  • Experience with Docker and containerized deployment.
  • Cloud experience with GCP/AWS/Azure.
  • Experience with vector databases and embeddings.
  • Develop scalable AI applications using Python and REST frameworks.

Responsibilities

  • Design and implement GenAI and LLM-based solutions.
  • Build RAG-based apps using retrieval, embeddings and vector databases.
  • Develop document processing solutions using OCR and DocAI.
  • Optimize AI workloads for production deployment and scalability.
  • Collaborate with teams to integrate AI-powered applications for enterprise use cases.

Skills

Python
NLP
ML
Deep Learning
PyTorch
LLMs
Vector databases
Semantic search
REST APIs
Cloud (GCP/AWS/Azure)

Tools

Google Vertex AI
Google Document AI
LangGraph/CrewAI
FastAPI
Flask
Docker

Job description

Quantum Technologies LLC is seeking a Lead Software Engineer focused on GenAI/GCP in Minneapolis, MN for an initial 6-month engagement with extension possible. The role offers a flexible, high-impact environment with a bill rate of $68/hour and multiple work arrangements (W-2, 1099, C2C).

The candidate will lead design and implementation of enterprise-grade GenAI solutions, build RAG apps, fine-tune LLMs, and deploy AI workloads on cloud platforms, using Python, FastAPI/Flask, and containerized

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