You will design and establish regional operational systems, processes, and capabilities to maintain infrastructure for physical AI solutions. This includes leading the expansion of client infrastructure hubs, managing client value operations, and ensuring consistent operational standards across global regions.
You will lead the end-to-end deployment and operation of cloud infrastructure for US customers, ensuring high availability and performance. Additionally, you will act as a technical liaison for enterprise IT organizations, managing security reviews and infrastructure governance.
You will act as a technical bridge between sales, product, and engineering teams to drive account growth and technical success. Responsibilities include conducting customer discovery, delivering customized demos, and leading proof-of-concepts for AI and data solutions.
The Principal Data Scientist will set the strategic vision and roadmap for AI/ML solutions within the Telecommunications domain to improve network performance and subscriber experience. They will lead the implementation of cutting-edge models, mentor data science teams, and collaborate cross-functionally to integrate intelligence into scalable products.
The Senior Data Scientist will research and develop machine learning models to solve complex healthcare challenges and improve patient outcomes. They will collaborate with cross-functional teams to integrate these models into production products and mentor junior data scientists.
Architect and build core capabilities for a Decision Intelligence Platform, including semantic engines, data platforms, and AI-powered systems. Lead the full engineering lifecycle from technical design to production operations across cloud-native and air-gapped environments.
The role focuses on accelerating automation coverage by converting manual test cases into robust automated regression scripts. Key duties include designing GraphQL API tests and maintaining a Playwright and TypeScript automation suite.
Design, deploy, and operate production Kubernetes clusters across cloud and on-premises environments to support critical health data systems. Implement GitOps-driven delivery, observability frameworks, and SRE practices to ensure high reliability and scalability.
