GenAI Lead-Minneapolis, MN and Hartford, CT

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David Miller

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Dec 11, 2025, 11:32:24 AM (6 days ago) Dec 11
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Job Title: GenAI Lead

Locations: Minneapolis, MN and Hartford, CT(2-3 Days)

Contract

Experience Required: 10+ Years


 

Must have LinkedIn.

 

Job Summary:

We are looking for a skilled GenAI Lead to drive the delivery of Generative AI initiatives, manage cross-functional teams, and oversee the implementation of AI solutions across enterprise environments. The candidate will work closely with business stakeholders, architects, and engineering teams to convert business use cases into production-ready GenAI solutions.

 

Key Responsibilities:

  • Lead end-to-end development and delivery of Generative AI projects.
  • Collaborate with product owners and SMEs to understand requirements and translate them into AI-driven solutions.
  • Guide teams in building RAG systems, LLM-powered applications, and automation workflows.
  • Oversee prompt engineering, model selection, fine-tuning, and performance testing.
  • Manage sprint planning, project execution, timelines, and reporting for AI initiatives.
  • Work with architects to ensure scalable and secure AI solution design.
  • Perform hands-on development when required in Python, ML frameworks, and cloud AI services.
  • Define and enforce AI development best practices, governance, and model evaluation standards.
  • Conduct PoCs and feasibility assessments for new GenAI use cases.
  • Present solution updates to leadership and stakeholders.

 

Must-Have Skills:

  • 10+ years of IT experience with 2–3+ years in AI/ML or GenAI.
  • Experience working with LLMs (GPT, Llama, Claude, Gemini, Mistral).
  • Strong knowledge of Prompt Engineering, RAG pipelines, and vector databases (Pinecone, FAISS, Weaviate, ElasticSearch).
  • Hands-on experience with Python, AI frameworks (LangChain, Hugging Face, TensorFlow, PyTorch).
  • Experience leading engineering teams and managing technical delivery.
  • Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent.
  • Strong understanding of MLOps, CI/CD, and model monitoring.
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