Senior Software Development Engineer in Test
Senior SDET building test automation, performance/load, and chaos engineering frameworks for Runpod's AI cloud platform — GPU Pods, serverless endpoints, GraphQL APIs, and Go services. Day to day: automation frameworks, CI/CD test pipelines, fault injection, and observability analysis with engineering and SRE teams.
- Compensation
- $175K–$200K / yr
- Location
- Remote - USA
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Contract
- Experience
- 10+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 10+ years of experience in QA Automation, SDET, software engineering, or a related technical field
- Expertise in testing cloud-scale distributed systems with focus on reliability, performance, and scalability
- Strong programming skills in at least one language, preferably Python, Golang, or TypeScript
- Hands-on experience 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 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.)
- Successful completion of a background check
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
Full description
Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform. The platform has processed more than 20 billion inference requests. We closed a $100M Series A in June 2026. We're at an inflection point for AI infrastructure, and we're building the platform the next generation of developers will depend on.
We're a small, remote-first team. We take ownership seriously, move fast, and ship work that more than a million developers rely on every day. We're looking for people who care deeply, build with urgency, and want to matter at scale.
Learn more in our CEO's funding announcement: .
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 one of the first engineers on Runpod’s QA team, you’ll have a unique opportunity to shape our testing strategy, automation frameworks, and quality standards as we scale. You’ll work across our entire platform, including GPU Pods, Serverless endpoints, batch jobs, Instant Clusters, storage, and billing systems. Our infrastructure spans GraphQL APIs, Go services running on thousands of GPU hosts worldwide, and complex event-driven pipelines.
Quality is embedded directly into our engineering process, not treated as a final checkpoint. You’ll collaborate closely with Engineering and SRE teams to review code, build integration and end-to-end tests, and identify issues before they reach production. We take a data-driven approach to quality, prioritizing measurable results, actionable insights, and continuous improvement.