Middle Infrastructure Engineer

Middle Infrastructure Engineer (ML/AI)About Workato Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility. Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in todays fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com. Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. Thats why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you Also, feel free to check out why: - Business Insider named us an enterprise startup to bet your career on - Forbes Cloud 100 recognized us as one of the top 100 private cloud companies in the world - Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America - Quartz ranked us the #1 best company for remote workers Responsibilities Our Team International Sr-level professionals from all over the Globe, experienced in building high-performing, scalable, enterprise-grade applications. Unique team of multinational professionals with integration, cloud, and consumer experience. We are currently seeking a promising Middle Infrastructure Engineer with experience in the AI domain. As a Middle Infrastructure Engineer, you will be responsible for deploying, scaling, and maintaining services for the ML/AI team. You will closely work with ML Engineers and Data Scientists as part of a small, flexible team and will have a direct impact on the modernization and maturation of the platform, including infrastructure architecture decisions. Requirements Qualifications / Experience / Technical Skills - BS/MS degree in Computer Science, Engineering or a related subject (or equivalent experience) - 3-5 years professional experience in hands-on engineering roles (DevOps/SRE) - 6+ months of experience with hosting AI models (ML flow, AWS SageMaker, Azure AI, Kubernetes) is preferred - 6+ months of experience with ML Ops (ML flow, vector databases (Qdrant), Dagster) is preferred - Kubernetes Expertise: Strong experience managing Kubernetes clusters and workloads, specifically using EKS (Elastic Kubernetes Service) - Programming Skills: Proficiency in Python language is essential. Ability to program in other languages such as Go, Ruby, or JavaScript is a plus Soft Skills / Personal Characteristics - Readiness to communicate in English with your colleagues SageMaker, Kubernetes, EKS, Python