Director of Engineering – AI/ML - CDH - Remote

Mayo Clinic•Rochester, MN

1d•Remote

About The Position

The Director of AI Engineering leads the strategy, design, and implementation of advanced artificial intelligence solutions across the organization. This role oversees teams responsible for building scalable AI models, integrating machine learning into products, and ensuring ethical and compliant AI practices. The director collaborates with product, data, and engineering leaders to drive innovation, optimize performance, and deliver AI capabilities that enhance customer experience and business outcomes. This role will lead a team of approximately 25+ engineers and manage engineering delivery of several products. Digital Product and Platform Leadership: Lead the full product lifecycle: strategy, prioritization, development, deployment, and evolution. Ensure alignment between business strategy, clinical operations, and end-user needs. Apply Agile methodologies to deliver scalable, high-impact digital solutions. Translate user insights into actionable roadmaps that shape clinical and consumer-facing platforms. Familiarity with regulatory standards (e.g., HIPAA, WCAG), especially in healthcare settings. Experience Design and Research: Champion a culture of user-centricity and evidence-based decision-making. Lead persona development, journey mapping, and usability testing efforts. Oversee the execution and maturation of experience design research methodologies, tools, and process standardization. Apply service design principles to identify friction points and inform optimization strategies. Design Systems and Content Strategy: Oversee governance and scalability of enterprise-wide design systems and UX standards. Drive creation and maintenance of reusable UI components, accessibility standards, and brand guidelines. Collaborate with engineers and designers to ensure a consistent and inclusive digital presence. Develop content strategy frameworks to support institutional communication and engagement. Information Security Leadership: Partner with technical teams and compliance leaders to guide cybersecurity priorities. Provide governance for enterprise information security policies and tools. Support incident response and risk mitigation activities with tactical leadership. Promote a culture of data stewardship, awareness, and proactive threat response. Team Leadership and Organizational Development: Track record of innovation in complex, matrixed environments. Demonstrated ability to navigate ambiguity and lead through change. Build and nurture high-performing, diverse teams across geographies and disciplines. Mentor and develop team members, instilling accountability and innovation. Establish measurable goals, support professional development, and promote collaboration. Drive operational excellence through structure, planning, and transparency. Team Leadership and Organizational Development: Track record of innovation in complex, matrixed environments. Demonstrated ability to navigate ambiguity and lead through change. Build and nurture high-performing, diverse teams across geographies and disciplines. Mentor and develop team members, instilling accountability and innovation. Establish measurable goals, support professional development, and promote collaboration. Drive operational excellence through structure, planning, and transparency. Core Technical Skills: Deep understanding of machine learning algorithms, supervised/unsupervised learning, and reinforcement learning. Expertise in deep learning architectures (CNNs, RNNs, Transformers). Strong grasp of natural language processing (NLP), computer vision, and recommendation systems. Familiarity with model versioning and continuous training pipelines. Advanced skills in Python and libraries like TensorFlow, PyTorch, Scikit-learn. Knowledge of distributed computing frameworks (Spark, Ray, etc.). Hands-on experience with cloud AI services (AWS SageMaker, Azure ML, GCP AI Platform). Knowledge of Generative AI (LLMs, diffusion models). Familiarity with edge AI and real-time inference. Experience with AI compliance frameworks and model interpretability tools (SHAP, LIME). Knowledge of AI ethics, bias mitigation, and explainability. Familiarity with privacy regulations (GDPR, CCPA) and secure data handling. Leadership & Strategic Skills: Experience in building and scaling AI engineering teams. Strong stakeholder management and ability to translate complex AI concepts into business value. Vendor evaluation and partnerships with AI technology providers. 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

Deep understanding of machine learning algorithms, supervised/unsupervised learning, and reinforcement learning.
Expertise in deep learning architectures (CNNs, RNNs, Transformers).
Strong grasp of natural language processing (NLP), computer vision, and recommendation systems.
Familiarity with model versioning and continuous training pipelines.
Advanced skills in Python and libraries like TensorFlow, PyTorch, Scikit-learn.
Knowledge of distributed computing frameworks (Spark, Ray, etc.).
Hands-on experience with cloud AI services (AWS SageMaker, Azure ML, GCP AI Platform).
Knowledge of Generative AI (LLMs, diffusion models).
Familiarity with edge AI and real-time inference.
Experience with AI compliance frameworks and model interpretability tools (SHAP, LIME).
Knowledge of AI ethics, bias mitigation, and explainability.
Familiarity with privacy regulations (GDPR, CCPA) and secure data handling.
Experience in building and scaling AI engineering teams.
Strong stakeholder management and ability to translate complex AI concepts into business value.
Vendor evaluation and partnerships with AI technology providers.
Track record of innovation in complex, matrixed environments.
Demonstrated ability to navigate ambiguity and lead through change.

Responsibilities

Lead the strategy, design, and implementation of advanced artificial intelligence solutions across the organization.
Oversee teams responsible for building scalable AI models, integrating machine learning into products, and ensuring ethical and compliant AI practices.
Collaborate with product, data, and engineering leaders to drive innovation, optimize performance, and deliver AI capabilities that enhance customer experience and business outcomes.
Lead a team of approximately 25+ engineers and manage engineering delivery of several products.
Lead the full product lifecycle: strategy, prioritization, development, deployment, and evolution.
Ensure alignment between business strategy, clinical operations, and end-user needs.
Apply Agile methodologies to deliver scalable, high-impact digital solutions.
Translate user insights into actionable roadmaps that shape clinical and consumer-facing platforms.
Lead persona development, journey mapping, and usability testing efforts.
Oversee the execution and maturation of experience design research methodologies, tools, and process standardization.
Oversee governance and scalability of enterprise-wide design systems and UX standards.
Drive creation and maintenance of reusable UI components, accessibility standards, and brand guidelines.
Collaborate with engineers and designers to ensure a consistent and inclusive digital presence.
Develop content strategy frameworks to support institutional communication and engagement.
Partner with technical teams and compliance leaders to guide cybersecurity priorities.
Provide governance for enterprise information security policies and tools.
Support incident response and risk mitigation activities with tactical leadership.
Promote a culture of data stewardship, awareness, and proactive threat response.
Build and nurture high-performing, diverse teams across geographies and disciplines.
Mentor and develop team members, instilling accountability and innovation.
Establish measurable goals, support professional development, and promote collaboration.
Drive operational excellence through structure, planning, and transparency.