Senior Software Development Engineer in Test

Runpod

Oregon

Hybrid

USD 175,000 - 200,000

Full time

10 days ago

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Benefits offered by this job

Equity in Runpod
Medical, dental & vision plans
Flexible PTO
Remote-friendly with Slack-based coll.
Home office stipend

Job summary

Runpod, the AI Developer Cloud, is seeking a Senior SDET to shape our testing strategy and automation as we scale. You will design and implement scalable test frameworks for cloud-scale distributed systems across GPU pods, serverless endpoints, and Kubernetes-based services.

You will drive performance, load, and chaos testing, integrate tests into CI/CD, and collaborate with engineering and SRE teams to ensure reliability and security at scale.

Qualifications

  • 10+ years of experience in QA Automation, SDET, software engineering, or related field.
  • Expertise in testing cloud-scale distributed systems with focus on reliability, performance and scalability.
  • Strong programming in Python, Golang, or Typescript.
  • Hands-on experience building test automation for microservices.
  • CI/CD, IaC, and automated deployment expertise.
  • Extensive experience with load testing tools (Locust, k6, JMeter) and observability (Prometheus, Grafana, OpenTelemetry, Datadog).
  • Proven experience testing containerized apps and Kubernetes environments.
  • Chaos engineering and fault-injection framework experience (Chaos Mesh, Gremlin, LitmusChaos).
  • Knowledge of distributed tracing and debugging in cloud-native environments.
  • Experience with message queues and event-driven architectures (Kafka, RabbitMQ, Redis).
  • Background check successful.

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 reliability of distributed services.
  • Develop and execute end-to-end integration, API, and system-level tests across microservices architectures.
  • Implement continuous testing pipelines within CI/CD to accelerate deployments.
  • Collaborate with development, SRE, and infra teams to embed quality practices in SDLC.
  • Analyze logs, telemetry, and observability data to identify and mitigate failures.
  • Drive automation of security testing, API contract validation, and infra testing.
  • Participate in on-call rotations to diagnose production reliability and performance issues.

Skills

QA Automation
SDET
Cloud-scale systems
Python
Golang
Typescript
CI/CD
IaC
Observability
Kubernetes
Chaos engineering

Education

Bachelor's degree in CS/Engineering

Tools

Locust
k6
JMeter
Prometheus
Grafana
OpenTelemetry
Datadog
Chaos Mesh
Gremlin
LitmusChaos
Kafka
RabbitMQ
Redis

Job 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: .

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.

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
  • 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.
What You'll Receive
  • The competitive base pay for this position ranges from ($175,000 - $200,000). This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location
  • Meaningful equity in a fast-growing company- everyone on the team receives stock options — your impact drives our growth, and you share in the upside.
  • Generous medical, dental & vision plans
  • Flexible PTO- take the time you need to recharge
  • Most roles are remote work first with an inclusive, collaborative teams utilizing slack as the main form of internal communication
  • Join a passionate team on the cutting edge of AI infrastructure — where culture, learning, and ownership are at the heart of how we scale.
  • $1,200 Home Office & Equipment Stipend-We set you up for success from day one with gear and support to create your ideal workspace

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. We welcome every qualified candidate eligible to work in the United States; however, we are currently unable to sponsor employment visas.

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