RunPod is pioneering the future of AI and machine learning, offering cutting-edge cloud infrastructure for full-stack AI applications. Founded in 2022, we are a rapidly growing, well-funded company with a remote-first organization spread globally. Our mission is to empower innovators and enterprises to unlock AI's true potential, driving technology and transforming industries. Join us as we shape the future of AI.
We are seeking a highly skilled and experienced Software Development Engineer in Test (SDET) to join our team. This role is pivotal in ensuring the reliability, scalability, and performance of our large-scale distributed systems. The ideal candidate will have a deep understanding of cloud-native architectures, automation-first testing strategies, and expertise in validating complex, high-performance infrastructure.
Key Aspects of Our Testing Approach:
- Automation-Driven Quality: We prioritize automated testing strategies to validate system performance, scalability, and reliability, reducing manual effort and increasing test coverage.
- Resilience Testing at Scale: Our SDETs proactively design tests to assess fault tolerance, high availability, and self-healing capabilities across globally distributed environments.
- Performance and Load Testing: We build and execute sophisticated test strategies to ensure our infrastructure scales efficiently under extreme workloads.
- Shift-Left Testing: We integrate testing early into the development lifecycle, ensuring quality and reliability from the inception of new features.
- Data-Driven Decision Making: We leverage metrics, analytics, and real-world traffic patterns to continuously refine our testing methodologies and improve system reliability.
As an SDET in our team, you will be at the forefront of cloud-scale system validation, developing innovative testing frameworks, stress-testing distributed architectures, and ensuring seamless deployments through automation and best practices.
Responsibilities:
- 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.
Requirements:
- 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.
Preferred:
- 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.
What You’ll Receive:
- The competitive base pay for this position ranges from $131,000 - $170,000. Factors that may be used to determine your actual pay may include your specific job related knowledge, skills and experience
- Stock options
- The flexibility of remote work with an inclusive, collaborative team.
- An opportunity to grow with a company that values innovation and user-centric design.
- Generous vacation policy to ensure work-life harmony and well-being.
- Contribute to a company with a global impact based in the US, Canada, and Europe.
RunPod is committed to maintaining a workplace free from discrimination and upholding the principles of equality and respect for all individuals. We believe that diversity in all its forms enhances our team. As an equal opportunity employer, RunPod is committed to creating an inclusive workforce at every level. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, protected veteran status, disability status, or any other characteristic protected by law.
