Aleksandr Sandrovskii

In a career of over 15 years as a software and systems engineering leader at enterprise technology leaders such as Amazon (AWS), I have acquired extensive experience in driving the end-to-end project and software development lifecycles to deliver scalable enterprise technology solutions (including applications, systems, and infrastructure) that enable business transformation. I excel in utilizing Agile tools and AI/ML technologies to foster solutions innovation, drive efficiencies across the SDLC, ensure on-time and on-budget solutions delivery, and facilitate effective management of multi-project portfolios. I am also a highly engaged, collaborative, and hands-on team leader with a track record of building and managing cross-functional, globally distributed teams from various cultures and backgrounds. Career Highlights: ★ Reduced hardware fleets in the AWS Transcribe streaming service by creating a service that enabled switching of locale-specific deep learning models in 100ms, resulting in a 2x reduction in fleets, a lower operational load, and 20% better hardware utilization. ★ Improved engineer productivity at AWS by identifying major pain points, discussing them with senior engineers from 8 teams, creating a best practices document, and communicating best practices across the organization, resulting in: o A 50% reduction in time taken by developers to deploy or repair their personal infra stacks. o An 80% reduction in test branch deployments to shared pre-prod stages. ★ Improved the accuracy of language predictions from under 70% to 85% to launch the ML-based automatic language identification feature at AWS and guided engineers in integrating the feature with the core software. ★ Developed and executed a module to automatically scale private clusters according to the needs of a workflow during the runtime at Amazon, substantially improving hardware utilization and reducing costs by 50%+ on average. ★ Refactored and improved the accuracy of tracking the key indicators of website performance (impressions, clicks, CR, and revenue) at Lazada by 10-15%. ★ Designed and developed an AB-testing framework adopted across Lazada to test hundreds of new features, ML models, and UI changes while designing a module for a “soft launch” and split-testing of new features and arbitrary configuration options.