GENERAL SUMMARYAs a key member of the Digital Enablement Hub, Henry Ford Health's enterprise AI & Automation Center of Excellence, the AI Engineer is responsible for designing, developing, deploying, and supporting enterprise-grade Artificial Intelligence solutions that drive innovation, efficiency, and business value across the organization. This role focuses on developing modern AI applications leveraging Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Optical Character Recognition (OCR), Machine Learning, Deep Learning, Natural Language Processing (NLP), and Model Context Protocol (MCP)-enabled integrations. The AI Engineer partners with business stakeholders, architects, data engineers, software developers, and operational teams to deliver scalable, secure, and responsible AI solutions aligned with organizational objectives and healthcare compliance requirements.
EDUCATION & EXPERIENCE: - Bachelor's degree in computer science, Artificial Intelligence, Data Science, Information Technology, Engineering, Mathematics, Statistics, or a related field.
- Master's degree in Artificial Intelligence, Computer Science, Data Science, or a related discipline preferred
- 0-4 years of professional experience in AI engineering, software engineering, machine learning, automation, data science, or a related technical field. Experience developing applications using Python or similar programming languages preferred.
- Experience with Generative AI technologies, Large Language Models (LLMs), AI Agents, Agentic AI, Natural Language Processing (NLP), or Retrieval-Augmented Generation (RAG) preferred.
- Experience with Optical Character Recognition (OCR), intelligent document processing, or document understanding solutions preferred.
- Experience implementing or integrating Model Context Protocol (MCP) servers, tools, or AI orchestration frameworks preferred.
- Experience with Microsoft Azure AI services including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Document Intelligence, Azure Machine Learning, or related technologies preferred.
- Experience with cloud-native application development and deployment preferred.
- Familiarity with MLOps, LLMOps, CI/CD pipelines, model deployment, monitoring, and observability preferred.
- Understanding of APIs, microservices, containers, and modern cloud architectures preferred.
- Knowledge of healthcare data, privacy, security, HIPAA, and regulatory requirements preferred.
- Familiarity with Power BI or other data visualization tools preferred.
- Strong analytical, problem-solving, communication, and presentation skills.
- Demonstrated ability to learn new technologies quickly and adapt in a rapidly evolving AI landscape.
- Ability to work independently and collaboratively in cross-functional Agile teams.
