QA Engineer - Observability & Monitoring

We are the Intelligent Internet Platform. We connect People, Places and Things anywhere, managing Internet Performance better than anyone else, while providing One Global Experience, giving Visibility, Control and Security through expereoOne.

Expereo believes in the power of Internet connectivity. As the world's largest provider of managed internet, SD-WAN/SASE, and Cloud connectivity solutions, we power enterprises and government sites worldwide, helping to enhance every business' productivity with flexible and optimal Internet performance.

As a trusted partner of Fortune 500 enterprises and carriers, our continued aim and success in helping both our customers and partners depends solely on the talented individuals that make Expereo a dynamic, effective, multicultural, and equitable environment.  

About the role

We are looking for a QA Engineer to join our Observability & Monitoring team. The team builds and operates internal, custom monitoring and observability platforms that provide deep visibility into our services, enabling proactive detection, faster incident resolution, and improved reliability across the company. 

In addition to monitoring and observability, the team owns an event driven automation platform, which is a key part of our strategy to move from reactive operations to proactive and automated workflows. This platform is actively evolving and expected to grow in scope and impact over time. 

You will work closely with software engineers and DevOps on systems that process metrics, logs, events, alerts, and automation workflows at scale. Quality, correctness, and reliability are central to what we build, and QA plays a key role throughout the entire development lifecycle. 

We work in a hybrid remote model, combining in office collaboration with the flexibility of remote work. 

What you’ll do 

• Define and execute test strategies for observability, monitoring, and automation platforms 

• Design, implement, and maintain automated tests for APIs, integrations, and end to end flows 

• Validate the correctness, consistency, and reliability of metrics, logs, and events 

• Test dashboards and visualizations built with Grafana and Kibana 

• Verify alerting and event driven automation logic, ensuring accurate detection and reliable automated actions 

• Test data flows across timeseries and relational storage layers 

• Collaborate closely with developers to embed quality early (“shift left”) 

• Participate in incident reviews and root cause analysis to prevent regressions 

• Contribute to improving QA practices as the automation platform grows in complexity and criticality 

Our tech stack 

• Elastic stack (search, indexing, logs, events) 

• Kibana dashboards and visualizations 

• Grafana dashboards and alerting 

• Influx DB (timeseries data) 

• PostgreSQL (relational data storage) 

• Python services and test automation 

• Kubernetes (container orchestration)  

• AWS (cloud hosting) 

• Graph QL/Rest APIs and backend services supporting a custom, inhouse monitoring framework 

• Event driven automation platform and workflows 

• Gitlab CI/CD pipelines with automated quality gates