Director or Manager of AI Engineering

Are you a technical leader and prior Programmer that is savvy in technical AI Engineering abilities and naturally showcase Leadership skills amongst a technical group? If so, and if you have been part of an AI Departmental Start up that required hands on coding and code review at a micro-level, as well as a tactical macro-level vision, THEN APPLY NOW. This role will require tight collaboration with the C Suite and VP Level Technical Executives and will require a residence in the Tampa Bay, FL Area for hybrid in-office/remote collaboration. We are looking for an experienced AI/ML leader to guide the design, deployment, and evolution of enterprise-scale machine learning capabilities for a healthcare-focused organization in Saint Petersburg, Florida. This role blends strategic leadership with practical engineering oversight, making it ideal for someone who can shape long-term vision while staying close to technical execution when needed. The successful candidate will help build reliable data and machine learning solutions that improve operational performance, enable advanced analytics, and support innovation across the business.Responsibilities:• Lead the AI/ML engineering function, setting technical direction for model development, deployment standards, and platform maturity across the organization.• Partner with data science, engineering, and business stakeholders to turn operational and analytical needs into scalable machine learning solutions.• Oversee the design and maintenance of end-to-end machine learning pipelines, including data ingestion, transformation, training, validation, and production monitoring.• Provide hands-on guidance for complex technical initiatives, stepping into architecture reviews, implementation planning, and troubleshooting when necessary.• Drive the use of modern big data and distributed processing technologies such as Spark, Hadoop, Kafka, and Databricks to support high-volume data workflows.• Establish engineering best practices for production-grade AI systems, with emphasis on reliability, performance, governance, and maintainability.• Direct the development and optimization of ETL processes that prepare structured and unstructured data for advanced modeling and analytics use cases.• Mentor and grow technical teams by fostering strong delivery habits, cross-functional collaboration, and continuous improvement in machine learning engineering.• Evaluate emerging tools, frameworks, and platform capabilities to strengthen the organization’s applied AI roadmap and execution model.