1

Retrieval Augmented Generation Rag Jobs in Minnesota

Contribute to AI chatbot and Retrieval-Augmented Generation (RAG) initiatives when applicable. Work Model We believe hybrid work is the way forward as we strive to provide flexibility wherever ...

New

Lead the design, development, and deployment of complex AI solutions, including LLM-based applications, retrieval-augmented generation (RAG) pipelines, and model-driven services. * Own technical ...

Showing results 21-40

Retrieval Augmented Generation Rag information

What are popular job titles related to Retrieval Augmented Generation Rag jobs in Minnesota?

For Retrieval Augmented Generation Rag jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Retrieval Augmented Generation Rag jobs in Minnesota look for?

The top searched job categories for Retrieval Augmented Generation Rag jobs in Minnesota are:

AI/ML Tech Lead / Architect - Gen AI & Agentic AI)

Nanda Technologies

Minneapolis, MN • On-site

Contractor

Re-posted 19 days ago


Job description

Email: paul@nandatechnologies.com

Job ID: JPC 6845-1-11/17

Job Title: AI/ML Tech Lead / Architect (Gen AI & Agentic AI)
Location: Minneapolis, MN (Onsite – Local Candidates Only)

Required exp: 12+ years

Visa: USC, GC, H4EAD
Client: Optum
Duration: Long-Term Contract

Key Responsibilities

  • Lead the architecture, design, and development of AI/ML, Gen AI, and Agentic AI solutions.
  • Provide hands-on technical leadership to engineering and data science teams.
  • Architect scalable and secure AI systems, integrating LLMs, vector databases, and agent frameworks.
  • Collaborate with product, data, and engineering teams to define technical roadmaps and solution strategies.
  • Oversee deployment, optimization, and performance tuning of AI solutions in production environments.
  • Ensure adherence to enterprise standards, security guidelines, and best practices.

Required Skills

  • 10+ years of experience in AI/ML engineering, solution architecture, or related roles.
  • Deep expertise in Generative AI, LLMs, prompt engineering, and Agentic AI systems.
  • Strong hands-on experience with Python, ML frameworks (TensorFlow, PyTorch), and LLM ecosystems.
  • Experience with vector databases (FAISS, Pinecone, Weaviate, etc.) and retrieval-augmented generation (RAG).
  • Solid understanding of cloud platforms (AWS/Azure/GCP) and MLOps pipelines.
  • Proven background in architecting enterprise-grade AI solutions.
  • Experience with multi-agent frameworks, orchestration tools, or autonomous agent systems.
  • Background in healthcare or payer/provider environments.
  • Certifications in AI/ML, cloud, or architecture disciplines.