Aleksandr Sherlygin

• Develop and deploy internal Python services for offshore wind operations. • Use Git, Azure DevOps and CI/CD workflows for version control and releases. • Containerize applications with Docker and deploy them to physical Linux servers. • Configure runtime environments and troubleshoot application, container, Linux and network issues. • Monitor services with Prometheus and automate operational workflows using Python and REST APIs.

• Automated image-labeling and validation workflows for ML pipelines using Python. • Developed data preprocessing and integration scripts to support reproducible model training and testing. • Applied Git-based version control, pipeline monitoring, and reproducibility practices across research workflows. • Collaborated with researchers and engineers on AI automation and prototype deployment.

Automated Python-based simulation workflows for distributed energy systems, reducing manual setup and execution effort. • Built and maintained containerized environments for reproducible development and testing. • Optimized simulation components, reducing runtime from ~2 min to ~45 sec. • Integrated API-based data flows and monitored distributed services, troubleshooting runtime and connectivity issues. • Developed and maintained 10+ simulation controllers in the Mosaik framework.

• Owned 100+ Linux VMs on VMware for enterprise test environments. • Operated and troubleshot TeamCity CI/CD workflows integrated with Git repositories. • Supported containerized microservices on OpenShift (Kubernetes), working with Docker images, pods, deployments and logs. • Defined server/database sizing, network access, firewall rules, certificates and security-zone connectivity. • Performed Linux readiness, access and connectivity checks.