Distinguished Enterprise Architect - Robotics

Why Mayo Clinic

Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans– to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

• Medical:
  
  Multiple plan options.
• Dental:
  
  Delta Dental or reimbursement account for flexible coverage.
• Vision:
  
  Affordable plan with national network.
• Pre-Tax Savings:
  
  HSA and FSAs for eligible expenses.
• Retirement:
  Competitive retirement package to secure your future.

Robots already work at Mayo Clinic, cleaning our floors, moving millions of laboratory specimens, and assisting in our operating rooms. Yet this is less than one percent of what is possible. Over the next decade, robotics will advance from sensor-driven, single-purpose machines to AI-driven autonomous systems, including generalist and humanoid robots, and Mayo Clinic intends to lead across that entire continuum, from the operating room to the loading dock.

The Mayo Clinic Robotics Program exists to pioneer human-centered robotics that expands access and creates an empowered, safe, more personalized, and convenient experience for patients and staff, cementing Mayo Clinic as the global leader in healthcare while freeing our people for the human work of healing. Within this program, the Distinguished Enterprise Architect - Robotics is the senior technical authority and the architect of how an entire enterprise of robots will work together.

Mayo's robotics future will not be built by a single vendor; it will be a growing, heterogeneous fleet from many manufacturers sharing the same corridors, elevators, laboratories, and operating rooms. This architect defines the enterprise standards, reference architecture, and vendor evaluation framework that make such a fleet coherent: how robots interoperate, how their data is owned and shared, how they are observed and orchestrated across vendors, and how they meet Mayo's expectations for safety, security, and reliability.

The role sets multi-year technical direction for the shift toward AI-driven autonomy and ensures that everything built or bought today becomes a foundation rather than a dead end.

• Bachelor's degreein computer science,information systems,systems engineering,or other relevantdegreesand(15) fifteen years of relevant technologyexperiencerequired.
• Master'sdegreein computer science, information systems, systems engineering, or other relevant degreeanddemonstratedarchitecture or technical leadership as a Principal, Chief, Distinguished, Fellow, or equivalent senior technical authority preferred.
• TOGAF Enterprise Architecture Practitioner or TOGAF 9 Certified certification isrequiredwithin 12 months of employment.
  
  TOGAF EA Leader credential is preferred.

• Deep, demonstrated expertise architecting multi-vendor robotics or cyber-physical systems at enterprise scale, spanning robot platforms, fleet management, connectivity, data, and security, rather than single-vendor or single-site deployments.
• Working command of robot interoperability standards and frameworks such as VDA 5050, Open-RMF, and OPC UA, and of healthcare data standards such as HL7 (including FHIR).
• Experience defining vendor evaluation frameworks, interoperability and data-rights requirements for procurement, and reference architectures that bind a multi-vendor ecosystem.
• Architecture experience with fleet observability, telemetry, and cross-vendor orchestration: the platforms through which an enterprise observes, measures, and coordinates heterogeneous robot fleets.
• Familiarity with mobile and service robot safety standards such as ANSI/A3 R15.08, ISO 3691-4, and ISO 13482, and cybersecurity frameworks for connected medical and operational technology such as ISA/IEC 62443 and IEC 81001-5-1.
• Perspective on the shift toward AI-driven autonomy (generalist and humanoid systems, learning-based methods, and simulation) sufficient to set multi-year technical direction and guardrails.
• Healthcare or other safety-critical, highly regulated environment experience; recognized external presence through standards bodies, publications, patents, or industry leadership.

Exempt

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