Sr. Platform Engineer

Reporting to the Director - Platform Technology Mayo Clinic Platform, the Senior Platform Engineer develops foundational infrastructure, automation, and software to enable platform functionality supporting the full sets of research, development, hosting and integration capabilities on Mayo Clinic Platform.

Under the direction of the Director - Platform Technology and the Principal Platform Integration Engineer, this team member will support the direct execution and delivery of technical aspects of Mayo Clinic Platform’s technology roadmap.

The position will be responsible for the following essential functions:

• Design, build, and operate infrastructure primarily on Google Cloud, including networking, IAM, compute, storage, and managed data services
• Build, enhance, and manage the cloud control plane using Crossplane compositions and providers
• Author and maintain reusable Terraform modules with versioning, automated testing and policy validation
• Operate production Kubernetes clusters: versioning, capacity planning, networking, ingress, storage, autoscaling, and multi-tenancy controls
• Troubleshoot workload and cluster-level issues down to the node and container runtime
• Administer Linux systems, including hardened and managed node images, performance tuning, kernel and package management, systemd, networking, and filesystem troubleshooting
• Design, build, and maintain platform APIs, services, and controllers in Go that let product teams provision and manage cloud resources through self-service, with attention to API versioning, backward compatibility, and clear error handling
• Treat the platform as a product: gather requirements from consuming teams, define interfaces, version APIs
• Produce reference documentation, client examples, runbooks, and golden-path templates so adoption does not require a conversation with the platform team
• Build and maintain pipelines in GitHub Actions and Azure DevOps, including reusable workflows, templates, self-hosted runners, and secret management
• Implement GitOps-based deployment patterns and promotion flows across environments using tools such as Argo CD
• Reduce manual toil by automating provisioning, onboarding, certificate and credential rotation, and routine operational requests
• Write and maintain automated tests for both application and infrastructure code, and integrate dependency, container image, infrastructure-as-code, and static analysis scanning into CI
• Participate in design and code review, upholding standards for readability, testability, and maintainability across the team’s repositories
• Define and instrument SLIs and SLOs for platform services; build dashboards, alerting, logging, and tracing
• Participate in on-call rotation, lead incident response, and drive blameless postmortems
• Monitor and optimize cloud spend for owned services
• Maintain patching and vulnerability remediation cadence for base images, node pools, application dependencies, and Terraform and Crossplane provider versions
• Support compliance and audit requirements through policy-as-code and admission controls
• Apply least-privilege access and defense in depth across projects and clusters, including service accounts and Workload Identity, VPC Service Controls, private networking, and organization policy constraints
• Help shape and execute the Mayo Clinic Platform technical roadmap, providing technical input based on implementation experience, operational learning, and the needs of teams using the platform
• Collaborate with product partners to follow established Software Development Life Cycle and Product Development Life Cycle processes, helping keep technical delivery aligned with product goals and organizational requirements.
• Mentor engineers through pairing, design guidance, and code review, strengthening team practice in infrastructure as code, Go, and Kubernetes

The above statements describe the general nature and level of work only. They are not an exhaustive list of all required responsibilities, duties, and skills. Other duties may be added or assigned.

Minimum Education and/or Experience Required:

• Bachelor’s degree in a relevant information technology field or, in lieu of a degree, a minimum of 7 years of direct infrastructure, platform, or backend engineering experience of increasing complexity.
• 3-5 years of professional cloud engineering experience building and supporting production platform services.
• Experience delivering software within collaborative, cross-functional teams using iterative or Agile development practices.
• Production experience with Google Cloud Platform, or with another major cloud provider
• Experience designing, building, and operating APIs and backend services, including proficiency in Go or in another backend language with readiness to work primarily in Go.
• Production experience with infrastructure as code using Terraform
• Linux systems administration experience in a production environment.
• Experience with scripting languages such as bash and python
• Experience building and maintaining CI/CD pipelines, such as GitHub Actions or Azure DevOps.
• Familiarity with healthcare data, privacy, security, or interoperability concepts, or demonstrated experience applying secure engineering practices to sensitive data in another highly regulated domain.
• Demonstrated understanding of secure software development practices, including access control, data protection, auditability, responsible production-data handling, and timely escalation of security or compliance concerns.
• Ability to independently own services or components end to end, from design through production support, including problems that are ambiguous or span multiple teams.
• Strong problem-solving and communication skills, including the ability to seek context, incorporate feedback, identify risks, and explain technical decisions.

Additional Experience and/or Qualifications:

• Experience with Crossplane, Config Connector, or a similar control-plane approach to infrastructure provisioning.
• Working knowledge of healthcare privacy, security, and compliance requirements, including HIPAA.
• Experience with cloud-native application development and technologies such as Docker, Kubernetes, and service mesh or API gateway patterns.
• Experience contributing to the design of complex distributed systems, services, or technical integrations.
• Experience improving engineering practices through testing, automation, documentation, code review, or observability.
• Experience supporting teammates through pairing, technical guidance, or knowledge sharing.
• Experience with policy-as-code and admission control, such as OPA/Gatekeeper, Kyverno, or Sentinel.
• Experience with observability tooling such as Prometheus, Grafana, or OpenTelemetry.
• Experience operating in a multi-cloud or hybrid environment spanning Google Cloud and Azure.
• Google Cloud Professional Cloud Architect or Professional Cloud DevOps Engineer certification, or CKA/CKAD.

Desired Characteristics:

• Operates independently in ambiguous problem spaces, identifying constraints and proposing practical solutions.
• Makes thoughtful technical decisions by considering customer needs, business goals, maintainability, security, cost, and operational impact.
• Recognizes when a decision can be made independently and when broader technical or stakeholder alignment is needed.
• Communicates technical concepts, risks, and tradeoffs clearly to both technical and nontechnical audiences.
• Collaborates effectively across engineering, product, design, and other partner groups to clarify requirements and deliver sustainable solutions.
• Identifies dependencies and delivery risks early and works with the appropriate partners to resolve them.
• Sets technical direction within their area and constructively influences decisions in adjacent teams.
• Leads improvements, migrations, and technical change within a defined area, including sequencing, risk, and rollback planning.
• Strengthens team capability through thoughtful code review, documentation, feedback, and knowledge sharing.
• Demonstrates curiosity and a commitment to developing technical judgment, healthcare domain knowledge, and leadership skills.
• Biases toward automation and repeatable patterns over one-time fixes, and treats recurring operational toil as a defect to be engineered away.
• Treats security, privacy, and compliance requirements as design inputs rather than late-stage review items.