Senior Software Development Engineer in Test - Runpod

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. 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.

The Role

We are seeking a highly skilled and experienced Software Development Engineer in Test (SDET) to ensure the reliability, scalability, and performance of our large-scale distributed systems. 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.

Key Aspects of Our Testing Approach

• Automation-Driven Quality: We prioritize automated testing strategies to validate system performance, scalability, and reliability.
• Resilience Testing at Scale: Proactively design tests to assess fault tolerance, high availability, and self-healing capabilities across globally distributed environments.
• Performance and Load Testing: Build and execute sophisticated test strategies to ensure infrastructure scales efficiently under extreme workloads.
• Shift-Left Testing: Integrate testing early into the development lifecycle, ensuring quality from the inception of new features.
• Data-Driven Decision Making: Leverage metrics, analytics, and real-world traffic patterns to refine testing methodologies.

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.
• 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

• 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.).
• Successful completion of a background check.

Preferred Qualifications

• 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

• Competitive base salary ranging from $175,000 - $200,000.
• Meaningful equity in a fast-growing company (stock options for all team members).
• Generous medical, dental, and vision plans.
• Flexible PTO.
• $1,200 home office and equipment stipend.
• Collaborative remote-first environment utilizing Slack.