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.

• Travel to our Memphis campus for the interview process and orientation (if selected).
• Travel to Memphis to be on‑site once per quarter, and additionally as needed.

By applying, you acknowledge and agree to these travel requirements as a condition of employment.

• Lead the design and engineering of production‑grade AI systems, including LLM‑based and agentic solutions, that integrate with clinical, operational, and administrative platforms.
• Translate institutional goals and use cases into deployable AI architectures, defining system boundaries, APIs, infrastructure components, and operational dependencies.
• Ensure AI systems are designed for reliability, security, scalability, and maintainability within St. Jude’s enterprise architecture.

• Own the end‑to‑end lifecycle of AI systems from initial deployment through ongoing operation, optimization, and retirement.
• Lead production deployments and ensure AI solutions are safely integrated into existing workflows without disrupting clinical or operational processes.
• Establish and maintain monitoring, logging, and alerting to track system performance, usage, data drift, and failure modes.
• Diagnose and resolve production issues, working closely with IT, informatics, and platform teams to maintain uptime and trust.

• Implement technical controls that support responsible AI practices, including auditability, access controls, versioning, and human‑in‑the‑loop safeguards.
• Partner with analytics, information security, and governance teams to ensure AI systems align with institutional AI governance standards and regulatory expectations.
• Document system behavior, deployment patterns, and operational procedures to support transparency, audit readiness, and long‑term sustainability.

• Collaborate closely with data scientists, clinicians, informaticists, and business stakeholders to translate needs into robust, operational AI solutions.
• Serve as a technical mentor within Analytics Services, helping establish engineering standards, patterns, and best practices for enterprise AI.
• Stay current on emerging AI technologies, platforms, and engineering approaches, evaluating their applicability to healthcare and enterprise operations.

• Master’s degree in Computer Science, Computer Engineering, Data Science, Information Technology, or related field required.
• PhD in a related field preferred, especially where accompanied by demonstrated delivery of production AI systems.

• Minimum Requirement: 5 years in designing high level architectures and developing solutions for large scale AI/ML systems and/or building solutions for a product on AI/ML features and capabilities.
• Highly prefer 5+ years of experience designing architectures and building production‑grade AI/ML systems (not just prototypes), including deployment, monitoring, and ongoing operations in a regulated or high‑availability environment.
• 5+ years experience developing and deploying AI solutions using modern techniques (e.g., ML, NLP, LLM‑based systems), with demonstrated ability to integrate solutions into enterprise workflows and platforms.
• Proven experience with MLOps / LLMOps practices: CI/CD for models/prompts, model/version management, evaluation, drift monitoring, observability, incident response, and rollback strategies highly preferred.
• Experience implementing monitoring, logging, and alerting for AI systems (quality, latency, cost, safety signals), and…