Senior Software Development Engineer in Test
New
R
RunpodAI infrastructure
Location: Remote - USAFull-TimeSenior
SalaryThe competitive base pay for this position ranges from ($175,000 - $200,000). $1,200 Home Office & Equipment Stipend
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Job Details
- Experience
- 10+ Years of experience in QA Automation, SDET, Software engineering or a related technical field
- Required Skills
- PythonJMeterKubernetesQA AutomationTypeScriptGoCI/CD
Requirements
- Have 10+ years of experience in QA automation, SDET, software engineering, or a related technical field.
- Bring expertise testing cloud-scale distributed systems, with a focus on reliability, performance, and scalability.
- Have strong programming skills in at least one language, preferably Python, Go, or TypeScript.
- Have hands-on experience building test automation frameworks for complex microservices architectures.
- Understand CI/CD pipelines, infrastructure as code (IaC), and automated deployment strategies.
- Have experience with load-testing tools such as Locust, k6, or JMeter.
- Have experience with observability platforms such as Prometheus, Grafana, OpenTelemetry, or Datadog.
- Have experience testing containerized applications and Kubernetes-based environments.
- Have expertise in chaos engineering and fault-injection frameworks such as Chaos Mesh, Gremlin, or LitmusChaos.
- Know distributed tracing and debugging in cloud-native environments.
- Have experience with message queues, databases, and event-driven architectures such as Kafka, RabbitMQ, or Redis.
- Successfully complete a background check.
- Preferred: Bachelor’s degree in Computer Science, Engineering, or a related field.
- Preferred: Experience with multi-region cloud deployments in AWS, GCP, or Azure; security testing and compliance frameworks; or GPU/AI compute resources.
Responsibilities
- Design, develop, and maintain test automation frameworks for cloud-scale distributed systems.
- Architect performance, load, and stress tests to validate system resilience under high traffic.
- Build fault-injection and chaos engineering strategies to assess distributed-service reliability.
- Develop and execute end-to-end integration, API, and system-level tests across microservices architectures.
- Implement continuous testing pipelines within CI/CD workflows.
- Collaborate with development, SRE, and infrastructure teams to embed quality practices in the SDLC.
- Analyze system logs, telemetry data, and observability metrics to identify and mitigate potential failures.
- Automate security testing, API contract validation, and infrastructure testing.
- Participate in on-call rotations to help diagnose critical production issues related to reliability and performance.
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