Senior Software Development Engineer in Test

The role

You will design and maintain test automation frameworks for cloud-scale distributed systems. You will validate system resilience, performance, and scalability across the platform including GPU Pods and serverless endpoints.

What you will do

• Design, develop, and maintain robust test automation frameworks for cloud-scale distributed systems.
• Architect performance, load, and stress tests to validate system resilience under high traffic conditions.
• Build fault-injection and chaos engineering strategies to assess the reliability of distributed services.
• Develop and execute end-to-end integration, API, and system-level tests across microservices-based architectures.
• Implement continuous testing pipelines within CI/CD workflows to accelerate deployment cycles.
• Collaborate closely with development, SRE, and infrastructure teams to ensure quality best practices are embedded within the SDLC.
• Analyze system logs, telemetry data, and observability metrics to identify and mitigate potential failures before they impact production.
• Drive automation of security testing, API contract validation, and infrastructure testing.
• Participate in on-call rotations to assist in diagnosing critical production issues related to system reliability and performance.

Required qualifications

• 10+ Years of experience in QA Automation, SDET, Software engineering or a related technical field
• Expertise in testing cloud-scale distributed systems with a strong focus on reliability, performance, and scalability.
• Strong programming skills in at least one language, preferably Python, Golang, or Typescript.
• Hands-on experience in building test automation frameworks for complex microservices architectures.
• Deep understanding of CI/CD pipelines, infrastructure as code (IaC), and automated deployment strategies.
• Extensive experience with load testing tools (e.g., Locust, k6, JMeter) and observability platforms (e.g., Prometheus, Grafana, OpenTelemetry, Datadog).
• Proven experience in testing containerized applications and Kubernetes-based environments.
• Strong expertise in chaos engineering and fault injection frameworks (e.g., Chaos Mesh, Gremlin, LitmusChaos).
• Knowledge of distributed tracing and debugging in cloud-native environments.
• Experience working with message queues, databases, and event-driven architectures (Kafka, RabbitMQ, Redis, etc.)

Nice to have

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience with multi-region cloud deployments in AWS, GCP, or Azure.
• Familiarity with security testing and compliance frameworks.
• Background in managing fleets of GPU/AI compute resources.
• Strong analytical and problem-solving skills with a passion for improving system quality at scale.

Benefits

• Meaningful equity in a fast-growing company
• Generous medical, dental & vision plans
• Flexible PTO
• $1,200 Home Office & Equipment Stipend

Before you apply

• Successful completion of a background check
• We are currently unable to sponsor employment visas.

About the company

Runpod is the AI Developer Cloud used by more than one million developers to experiment, train, fine-tune, deploy, and scale AI. It is a small, remote-first team.