Senior Healthcare Artificial Intelligence (AI) Engineer, Analytics Hub

About the role

Join Our Analytics Hub
Our growing Analytics Hub works with our consulting teams to deliver new insights, streamlined analysis, and world-class intelligence to the healthcare organizations we serve as clients.

Responsibilities

• Design and develop production-grade generative AI, ML, and agentic AI solutions for healthcare and business applications.
• Collaborate with IT and Hub members to deploy solutions.
• Build retrieval-augmented generation systems, intelligent assistants, AI agents, and workflow automation solutions using enterprise and healthcare data.
• Develop evaluation frameworks that measure solution quality, accuracy, groundedness, reliability, and business impact.
• Contribute to the creation and improvement of automated testing methodologies, benchmark datasets, and regression testing processes to ensure AI solutions remain stable as prompts, models, and data sources evolve.
• Partner with business stakeholders (consultants, clients, business development, HR, etc.) to define success metrics and acceptance criteria for AI-powered applications.
• Evaluate emerging AI technologies and recommend architectures that balance performance, cost, scalability, and risk.

Qualifications

• Strong knowledge of and passion for the healthcare industry
• Bachelor’s degree in either computer science, computer engineering, mathematics, statistics, health information management, or a related degree that relies heavily on critical thinking, logic, and math
• A master's degree is a plus
• 5+ years of professional experience working in data engineering or data science
• Healthcare or consulting experience is preferred
• 2+ years of recent experience developing production AI, ML, or advanced analytics solutions
• Strong proficiency in: Python, SQL, and ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Microsoft Azure AI Services, Azure OpenAI, AWS, or Google Cloud AI; strong preference for Azure AI Services
• Experience developing and deploying LLM-based applications
• Experience with agentic AI frameworks and LLM evaluation frameworks
• Knowledge of MLOps, CI/CD pipelines, containerization (Docker), and cloud architecture
• Strong analytical, problem-solving, and communication skills