Padmi

Principal Engineer, Cloud Architecture

United StatesPosted 1 month ago
Software engineeringUnspecified
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Location: Hybrid - Iselin, NJ Medidata follows a hybrid office policy in which employees who are hired for an in-person position are expected to work on site a certain number of days per week following Company policy. About our Company: Medidata is powering smarter treatments and healthier people through digital solutions to support clinical trials. Celebrating over 25 years of ground-breaking technological innovation across more than 38,000 trials and 12 million patients, Medidata offers industry-leading expertise, analytics-powered insights, and one of the largest clinical trial data sets in the industry. More than 1 million registered users across approximately 2,300 customers trust Medidata's seamless, end-to-end platform to improve patient experiences, accelerate clinical breakthroughs, and bring therapies to market faster. A Dassault Systèmes brand (Euronext Paris: FR0014003TT8, DSY.PA), Medidata is headquartered in New York City and has been recognized as a Leader by Everest Group and IDC. Discover more at www.medidata.com . Listen to our latest podcast, from Dreamers to Disruptors, and follow us at @Medidata. About the Team: We are seeking a Distinguished Engineer, Cloud Architecture to lead the transformation of our R&D infrastructure into a hyper-automated, AI-driven engine. This is a "deep-dive" technical leadership role for an engineer-leader who views operations not as a series of manual tasks, but as a complex system to be optimized through code, data science, and architectural rigor. You will go beyond traditional capacity planning and governance. You will be responsible for reengineering the operational backbone of our hybrid cloud, shifting from manual resource allocation and reactive budgeting to a proactive, AI-augmented, and developer-centric infrastructure model. You will partner with the VP of Cloud Engineering to ensure our platform is technically sound, fiscally optimized, and ready for high-scale AI/ML workloads.

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