Senior Platform Engineer

Mayo Clinic • Rochester, MN

1d

About The Position

The Mayo Clinic Platform AI team is seeking an experienced Senior Platform Engineer to join our innovative efforts in developing and implementing cutting-edge generative AI solutions. In this role, you will lead the design and development of state-of-the-art generative AI models, establish comprehensive safety guardrails for responsible AI deployment, and drive the creation of autonomous AI agents. You’ll collaborate closely with a diverse team of data scientists, product managers, and engineers as we shape the future of AI applications while ensuring our systems remain safe, ethical, and scalable. Key Responsibilities Generative AI Model Development: Architect, design, and implement advanced generative AI models and architectures that support varied departmental applications and cutting-edge research initiatives. GenAI Safety & Ethics: Develop comprehensive safety guardrails and ethical guidelines to ensure responsible AI development and deployment, incorporating best practices in AI alignment and security. Cross-Functional Collaboration: Partner with cross-functional teams to integrate AI solutions seamlessly within the Mayo Clinic Platform, translating business needs into robust technical implementations. Autonomous AI Agents: Lead the creation and optimization of intelligent AI agents designed for autonomous decision-making, leveraging techniques in prompt engineering and model fine-tuning. System Enhancement: Evaluate and enhance existing generative AI deployments across departmental applications, continually iterating to improve performance, safety, and scalability. Performance Optimization: Identify bottlenecks in AI/ML pipelines and propose solutions to improve system performance, efficiency, and scalability. Monitoring & Troubleshooting: Develop and maintain observability tools, including logging, monitoring, and alerting, to diagnose and resolve production issues. Documentation: Create and maintain technical documentation, including architectural diagrams, API specifications, and onboarding guides for internal and external stakeholders. Thought Leadership: Stay updated with the latest trends and advancements in federated learning, distributed computing, and machine learning frameworks to continually enhance the platform. This vacancy is not eligible for sponsorship/ we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program

Requirements

• Bachelors degree in a relevant information technology field or a minimum 7 years of direct full-stack engineering with increasing complexity.
• 3-5 years working in diverse environments utilizing Agile principles of software development.
• Proven experience as a Full Stack Engineer with a strong emphasis on healthcare interoperability.
• Proficiency in Java and/or .NET for backend development, including API / service design and implementation.
• Expertise in Javascript with a focus on React and react frameworks (e.g. NextJS) for building responsive and intuitive front-end applications.
• Hands-on experience with Google Cloud Platform (GCP) (or equivalent) services and cloud-native application development.
• Familiarity with healthcare interoperability standards such as HL7, FHIR and OMOP.
• Strong problem-solving skills and the ability to work in a collaborative, cross-functional team environment.
• Experience with DevOps practices, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes) is a plus.
• Knowledge of healthcare data security and compliance requirements, including HIPAA, is highly desirable.
• Excellent communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
• A proactive and self-driven mindset with a passion for staying up-to-date with emerging technologies and industry best practices.
• Experience with Interoperability standards such as HL7, FHIR and OMOP.
• Experience with solutions integration/delivery in a healthcare setting.

Nice To Haves

• LLM Fine-Tuning: Experience in fine-tuning large language models and advanced prompt engineering techniques.
• AI Alignment & Safety: Hands-on background in AI alignment strategies and the development of robust safety mechanisms.
• RAG Expertise: Familiarity with Retrieval-Augmented Generation (RAG) techniques to improve model responsiveness and efficiency.
• Production Deployment: Proven experience with AI model deployment and scaling in production environments, including container orchestration and cloud-based solutions.
• Multi-Modal AI: Understanding and experience working with multi-modal AI systems that integrate text, image, and other data types.

Responsibilities

• Generative AI Model Development: Architect, design, and implement advanced generative AI models and architectures that support varied departmental applications and cutting-edge research initiatives.
• GenAI Safety & Ethics: Develop comprehensive safety guardrails and ethical guidelines to ensure responsible AI development and deployment, incorporating best practices in AI alignment and security.
• Cross-Functional Collaboration: Partner with cross-functional teams to integrate AI solutions seamlessly within the Mayo Clinic Platform, translating business needs into robust technical implementations.
• Autonomous AI Agents: Lead the creation and optimization of intelligent AI agents designed for autonomous decision-making, leveraging techniques in prompt engineering and model fine-tuning.
• System Enhancement: Evaluate and enhance existing generative AI deployments across departmental applications, continually iterating to improve performance, safety, and scalability.
• Performance Optimization: Identify bottlenecks in AI/ML pipelines and propose solutions to improve system performance, efficiency, and scalability.
• Monitoring & Troubleshooting: Develop and maintain observability tools, including logging, monitoring, and alerting, to diagnose and resolve production issues.
• Documentation: Create and maintain technical documentation, including architectural diagrams, API specifications, and onboarding guides for internal and external stakeholders.
• Thought Leadership: Stay updated with the latest trends and advancements in federated learning, distributed computing, and machine learning frameworks to continually enhance the platform.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees