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Planet DDS is a leading provider of a platform of cloud-based solutions that empowers growth-minded dental businesses. Now serving over 13,000 practices and 118,000 customers in North America, Planet DDS delivers a comprehensive suite of solutions, including Denticon Practice Management, Cloud 9 Ortho Practice Management, and Apteryx Cloud Imaging. Planet DDS is dedicated to enabling dental support organizations (DSOs) and groups to grow and thrive with technology that delivers seamless integrations, improved workflows, and future-proof scalability. We are seeking a Principal Infrastructure Architect to lead the design, deployment, and optimization of Planet DDS’s cloud and on-premises infrastructure. In this role you will influence the platform strategy for Planet DDS. You will advise the engineering and product leadership at the company. You will also work with the engineers to mentor them in choosing the right architectural patterns and technologies. You will be the hands-on champion for building an AI-powered infrastructure platform and will drive adoption of AI tooling in the platform organization.
Job Responsibility:
Drive adoption of AI-based DevOps tools to automate processes, optimize infrastructure, and enhance team productivity
Promote best practices for DevOps, SRE, Security, and Deployment platforms
Participate in incident retrospectives and drive operational excellence across the engineering teams
Participate in Incident Management and establish top notch incident communication practices
Partner with engineering leadership to build long term roadmap for the organization
Partner with the platform teams to drive architecture review of shared components
Leverage expertise in FinOps and cloud cost control to drive efficient utilization of cloud resources in the engineering organization
Partner with senior engineers across the company to drive best in class engineering practices across the organization
Requirements:
Bachelor’s degree in computer science or related field, or equivalent experience
7+ years of hands-on experience with Azure (required), AWS and GCP (preferred)
Minimum 1 years’ experience with AI coding tools
Experience with infrastructure as code tools and cloud security best practices
Experience in operating large scale critical systems
Deep experience with FinOps and cloud cost optimization
Strong written and verbal communication skills
Proven experience of driving best practices across engineering organization
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