Lead Python Automation QA Engineer

Description

Our client is an innovative manufacturer of medical devices in the United States, producing devices and software applications.

In this project, you will have a great opportunity to be involved in the full development life cycle of medical software, which is designed to assist individuals by processing information from medical devices to identify health trends and track daily activities. In addition, there are opportunities to work with medical devices, in the scope of end-to-end testing.

Requirements

• Proficiency in Python or Go (ideally both). Shell scripting and Terraform familiarity are a plus.
  Cloud & Infrastructure:
• Hands-on experience with AWS (IAM, SQS, RDS, Redis/ElastiCache, S3, SNS, Lambda, VPC).
• Experience validating infrastructure via Terraform or Terratest.
• Kubernetes fluency (namespaces, Helm, ConfigMaps, RBAC, Services, Pods, HPA).
• Experience designing black-box/gray-box tests for infrastructure and configuration correctness.
• Familiar with GitOps or Infrastructure-as-Code testing practices.
• Proficient with New Relic, OpenTelemetry, or similar platforms to track real-time application and resource performance.

• Experience designing and analyzing results from performance and load testing frameworks.

  Nice to have:
   

• Experience with service meshes (Istio, Linkerd) or sidecar observability.
• Familiarity with GitLab pipelines, Argo CD, and Helmfile/Helm charts.
• Background in SRE or DevSecOps practices.
• Experience with Cilium and eBPF observability, (layer 3, 4, and 7)

Job responsibilities

• Perform testing on software systems without user interfaces, focusing on API testing.
• Develop, execute, and maintain automated test scripts to ensure software quality and reliability.
• Write and maintain code. 
• Utilize Python for scripting and automation tasks.
• Use Selenium WebDriver for web application testing.
• Implement performance testing using Jmeter.
• Apply solid QA practices including black box testing, risk-based testing, system testing, regression testing, and exploratory testing to identify and resolve issues.