Generative AI Engineer - Fargo, ND

Job Title: Generative AI Engineer
Location: Fargo, ND
Domain: Banking
Duration: Long Term Contract
Looking for W2 Candidates. No C2C

About the Role:

We are seeking a Generative AI Engineer who is passionate about building cutting-edge AI applications using LLMs (Large Language Models), foundational models, and multi-modal architectures. This role is critical in driving our AI transformation strategy by developing intelligent solutions that solve real-world business problems in healthcare, insurance, and finance domains. You will work collaboratively with cross-functional teams including data scientists, ML engineers, DevOps teams, and product managers. Your expertise will shape the future of AI-assisted applications across intelligent document processing, member communication, claims automation, and clinical data analysis.

Responsibilities:

• Build, fine-tune, and deploy generative AI models including LLMs (GPT, BERT, T5, LLaMA, etc.).
• Develop prompt engineering strategies for RAG (Retrieval-Augmented Generation) and agentic workflows.
• Integrate Gen AI models with production pipelines using MLOps and CI/CD best practices.
• Work with large, unstructured datasets, including clinical notes, member records, and insurance claims.
• Collaborate with domain experts to translate business requirements into generative model specifications.
• Research and experiment with state-of-the-art methods in NLP, vision-language models, and self-supervised learning.
• Ensure responsible AI use by implementing model monitoring, fairness testing, and explainability techniques.
• Lead internal Gen AI workshops and mentor junior ML/AI team members.

Qualifications:

• Experience in machine learning and deep learning, with focused on generative AI applications.
• Deep expertise in Python and ML libraries such as Hugging Face Transformers, LangChain, PyTorch, and TensorFlow.
• Experience with Azure, AWS, or Google Cloud Platform platforms for scalable model deployment.
• Solid understanding of LLM tuning methods (LoRA, PEFT, QLoRA, adapters).
• Experience building RAG pipelines using vector databases like FAISS, Pinecone, or Weaviate.
• Hands-on with MLOps tools like MLflow, Kubeflow, Azure ML, or SageMaker.
• Strong knowledge of NLP techniques including summarization, question answering, translation, and sentiment analysis.
• Familiarity with vision language models and multimodal AI is a plus.
• Excellent communication and stakeholder engagement skills.

Preferred:

• Experience in Healthcare or Insurance domain preferred.
• Microsoft Azure AI Engineer or Data Scientist Associate certification.
• Experience working with de-identified PHI and HIPAA-compliant AI systems.