Worked in a team providing infrastructure for services and ML workloads. Within the team’s domain, I was responsible for designing and implementing a Kubernetes-based platform for services that was used to run tens of client solutions including mission-critical solutions.◦ Introduced solutions for observability, monitoring, and availability, improving the reliability of customers’ services. ◦ Initiated the deployment of object and block storage solutions in the organization, aimed to solve security, performance, and cross-site data accessibility issues for multiple customer teams.◦ Trained 20+ customer teams on Service Oriented Architecture and Kubernetes, ensuring their successful onboarding and optimal usage of the platform.◦ Reduced CI pipeline failures of key customers by up to 40% by deploying an internal Python Package Index.

◦ Developed tools for managing and tracking regression tests of chip-design kits.◦ Maintained and improved an application used to track the usage of tools developed in the organization.◦ Integrated Git with the organization’s release tool.

Camelog was a SaaS solution for liveness-testing of mobile advertisements. The service executed millions of dead-or-alive tests a day through API requests, scheduled jobs, and a dedicated website.◦ Developed an advertisement validation platform using Django and Puppeteer, and deployed on AWS (EC2, Lambda, API Gateway, DynamoDB). ◦ Reduced costs and improved the scalability of the system by migrating a major VM-based backend service to a serverless-based solution (AWS Lambda).