Andrei-Ioan Cirnu

Established CI/CD for a new Azure OpenAI project:

• Built and optimized GitLab pipelines for Docker images, versioning, branching , and container registry (including dependency proxy optimization).
• Created Helm charts for Kubernetes deployments ( private AKS ) and integrated Azure services such as Azure AGIC, Managed Identities, VM jumpboxes, private ACR, Key Vault, Gateways, Firewalls under a private networking model, with a private self-hosted runner
• Developed Terraform modules to automate the entire stack—both infrastructure and application—acting as the sole DevOps engineer and collaborating with PMs on resource and budget allocations and architected the cloud side of the application.

Migrated legacy projects from Bitbucket to GitLab:

• Transitioned Jenkins -based pipelines to GitLab pipelines.
• Established robust secrets management and streamlined code repositories.

Provided SRE and on-call support for two internal networking applications

• Implemented performance optimizations and comprehensive monitoring solutions ( Datadog , logs ingestion, alerting, synthetic tests).
• Managed AWS infrastructure while diving into networking and application code ( .NE T and Kotlin/Spring), identifying bugs and submitting improvements.

Leading development of a new distributed application (.NET, PostgreSQL, Hangfire)

• Contributing to both the application codebase and the infrastructure /CI/CD pipeline ( Aspire, Docker, GitLab CI/CD, Azure, Helm ).
• Collaborated in architecting the overall solution, balancing development and operations responsibilities.

• Developed and maintained a tool for deploying Azure VMs that are compliant, secure, and standardized. Users could deploy these VMs by selecting features from a front-end, while terraform would work as the IaC tool that would provide those resources
  While doing this work, I gained proficiency in Azure and its REST API, azure cli , and all things related to Azure and its resources such as Virtual machines, network interfaces, disks, storage accounts, key vaults, resource groups, subscriptions, managed identities, virtual networks, subnets, routing tables, load balancers, MSSQL Virtual machines, VM backup, ASR, Disaster Recovery
• Worked on the development side of the application using .NET Core , developed features with ASP.NET MVC, designed database tables and models for the features, interacted with those with EFCore. Developed API endpoints for the features, async workers and simple frontends to display the information.
• Leveraged Ansible to ensure that newly-deployed VMs were standardized, secure, and had the required tools installed. Created roles, custom Jinja2 templates and callback plugins for the Ansible playbooks.
• Created and maintained a pipeline in Azure DevOps to generate up-to-date images of the VMs on a daily basis
• Migrated the pipeline to GitHub Actions as a workflow for improved efficiency and maintainability
• Utilized Docker to create self-hosted runners inside containers that would run the workflow with their required tooling, while keeping the image size small
• Demonstrated proficiency in handling both Windows and Linux-specific work, as well as working with SSH, networking, firewalls, users and groups, registries for different policies, and so on.

• Continued development of both the automation framework and the monitoring tool
• Developed an API for the server, providing endpoints for user interaction with clients via HTTP requests
• Implemented a postgreSQL database for storing registered client information and collected data, using SQLAlchemy to interface with the database
• Deployed the server to Google Cloud Platform using Kubernetes and Docker for containerization

• Continued development of the internal automation tool while working with the automation team on an automation framework
• Set up multiple monitoring setups across multiple offices to support multiple teams in finding bugs and calculating reliability before big releases
• Improved reporting functionality using technologies such as the ELK stack, with logstash processing data from the tool and Kibana used to view the data
• Migrated to a client-server architecture , enabling teams to run their own client and interact with the tool instantaneously.

• Developed and maintained an internal automation tool to monitor a large number of devices over long periods of time
• Built the tool as a service using Python, HTTP, and Flask .
• Each separate process that would deal with one device was able to run simulations and different commands on the fitbit device. The flask server was on a separate thread from the main monitor service , while all devices were being simulated and monitored on entirely separate processes .
• Worked with Bluetooth, GPS , and serial connections to support the Fitbit technology stack
• Set up the Git repository and JIRA , created a roadmap, and wrote tickets to work in sprints, ensuring timely delivery of features