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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Development Engineer in Test - **Company:** QA+, Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $175,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Cloud Computing, Code Review, Computer Programming, Databases, Continuous Integration, Software Debugging, Decision Support Systems, Distributed Systems, Apache JMeter, Python (Programming Language), Load Testing, Systems Development Life Cycle, Queueing Systems, RabbitMQ, Redis, Reliability Engineering, E2e Testing, Cloud Services, Prometheus, Software Engineering, Software Testing Automation Framework, TypeScript, AI Infrastructure, Datadog, Grafana, Reliability of Systems, System-level Testing, Information Technology, Deployment Automation, Data Analytics, Apache Kafka, Graphql, Dynatrace, Serverless Computing, SDET, Golang, Microservices - **Published:** October 27, 2026 - **Apply:** https://www.builtincolorado.com/job/senior-software-development-engineer-test/11887466?handler=ApplyRedirect ## About the Role * 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: * 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. ## Description 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. As an SDET, you'll play a critical role in building scalable testing frameworks, validating complex distributed systems, stress-testing cloud infrastructure, and driving reliable deployments through automation. This is a high-impact opportunity to help establish the foundation of QA at Runpod while directly influencing the reliability, performance, and scalability of our growing platform., * 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.