Lead AI Engineer

Overview

St. Jude is where those with a passion for making a difference come to break new ground. Located in Memphis, Tennessee, the mission of St. Jude Children's Research Hospital is to advance cures, and means of prevention, for pediatric catastrophic diseases through research and treatment. We are leading the way the world understands, treats and defeats childhood cancer and other life‑threatening diseases.

We are looking for a Lead AI Engineer to join our Analytics Services team in supporting this incredible work.

The Lead AI Engineer will play a pivotal role in advancing healthcare artificial intelligence (AI) initiatives by developing and training AI tools aimed at automating and optimizing clinical workflows, operational efficiencies, and administrative tasks. As part of our dynamic team, your expertise in AI and other cognitive computing methodologies, such as but not limited to machine learning (ML), large language models (LLMs), small language models (SLMs), natural language processing (NLP), Generative AI, and Agentic AI, will help revolutionize pediatric healthcare.

This is your opportunity to design, develop, and deploy innovative AI solutions that directly enhance patient and family outcomes and leverage innovation to transform operational and administrative practices.

A day in the life of the Lead AI Engineer includes working with institutional stakeholders to deploy and integrate sophisticated AI systems, rigorously testing, validating, and tracking learning models, and troubleshooting issues to ensure system accuracy and reliability. A core objective of this role is to implement AI solutions that closely emulate human cognitive processes, thereby enhancing the reliability and efficacy of the problems that they are intended to solve without introducing biases, legal or ethical risks.

These solutions should enable resource optimization and enhance decision‑making, ultimately to support driving fulfillment of the St. Jude mission. As a leader, you will collaborate with analytics, data scientists, IT, informatics, and business stakeholders to ensure AI systems are scalable, secure, and seamlessly integrated into existing workflows.

This position may be eligible for the possibility of remote work.

• AI Engineering Design and Collaboration :
  Collaborate with clinical, operational and administrative leadership and project teams to design and architect AI‑powered systems that integrate with clinical and administrative platforms. Translate strategic goals into actionable AI pilot initiatives and scalable implementation plans. Consult with project teams to ensure engineering feasibility and alignment with enterprise infrastructure. Define technical requirements, APIs, and infrastructure components for deploying AI solutions. Ensure systems are modular, secure, and scalable across the institution.
• Deployment and Workflow Integration :
  Lead the deployment of AI solutions into production environments and ensure seamless integration with clinical and administrative systems. Collaborate with IT, informatics and clinical operations to ensure AI systems enhance - not disrupt - existing workflows. Establish monitoring protocols to ensure reliability, safety and user satisfaction. Optimize system performance, latency, and reliability in real‑world clinical and operational settings.
• Governance, Reliability and Communication :
  Implement monitoring, logging and alerting systems to ensure AI solutions are meeting safety, compliance and other standards. Enforce responsible AI practices, including auditability, access controls and human‑in‑the‑loop safeguards. Document system behavior, deployment protocols and integration are consistent with internal AI governance practices.
• Innovation and Continuous Learning: Stay current on advancements in agentic AI, cognitive architectures, and AI technologies. Evaluate emerging tools and platforms for enterprise relevance. Mentor peers and other Analytics Services staff and contribute to the development of internal best practices for AI engineering in healthcare.

• Master's degree in computer science, computer engineering,…