Software Quality Assurance Engineer - Cloud Services

Headquartered in the United States,
TP-Link Systems Inc. is a global provider of networking devices and smart home products, consistently ranked among the world’s leading providers of Wi‑Fi devices. Serving customers in over 170 countries, TP‑Link develops innovative technologies that connect millions of users and devices worldwide.

At TP‑Link, we believe technology can make life smarter, simpler, and more connected. We are committed to delivering high‑quality products and cloud services that power modern networking, security, and smart home experiences.

TP‑Link is seeking a Software Quality Assurance Engineer – Cloud Services to join our growing Cloud Services Quality Engineering team. In this role, you will contribute to quality initiatives for cloud platforms that support millions of connected devices and users worldwide.

You will contribute to quality planning, develop automated testing solutions, identify quality risks, and help ensure the reliable delivery of scalable cloud services across TP‑Link’s networking and smart‑home ecosystem. Working closely with software engineers, architects, product managers, and senior quality engineers, you will help build a strong quality culture while expanding your expertise in cloud‑native technologies and large‑scale distributed systems.

This role is ideal for an ambitious quality engineer who is passionate about cloud technologies, backend systems, automation, and building expertise in large‑scale distributed systems.

• Support quality planning, test strategy development, and test execution for cloud service projects and backend systems.
• Collaborate with senior engineers during requirement analysis, architecture reviews, and design discussions to identify quality risks and ensure testability of microservices and distributed systems.
• Design and develop test plans, test cases, and testing approaches based on business requirements, system architecture, and risk analysis.
• Validate cloud services through API, functional, integration, database, regression, and end‑to‑end testing.
• Investigate software issues using APIs, databases, logs, metrics, and distributed system workflows to isolate failures, support root cause analysis, and verify fixes.
• Execute and extend automated test scripts for API, integration, and end‑to‑end suites using Python or Java, leveraging AI‑assisted development and testing tools to improve test automation and engineering productivity.
• Assist with performance, scalability, reliability, and resiliency testing to help validate cloud services under varying workloads.
• Partner closely with software engineers, product managers, and architects throughout the software development lifecycle to deliver high‑quality releases.

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 2–5 years of experience in software quality engineering, backend system testing, or cloud service testing.
• Solid understanding of software testing principles and experience testing backend APIs and services.
• Understanding of microservices architectures and distributed systems, with the ability to analyze service interactions and develop effective test coverage.
• Experience testing RESTful APIs and validating backend services using API testing tools, databases, and log analysis.
• Experience testing applications deployed on AWS or other public cloud platforms.
• Proficiency in Python or Java, with experience developing, extending, and maintaining automated test frameworks and test suites.
• Basic understanding of CI/CD pipelines, Git, Docker, Kubernetes, and modern cloud deployment workflows.
• Familiarity with performance, scalability, reliability, and resiliency testing concepts and tools.

• Experience owning quality and testing of a software component or cloud service module.
• Experience testing event‑driven or distributed systems using technologies such as Kafka, RabbitMQ, or similar messaging platforms.
• Familiarity with backend technologies such as MySQL, MongoDB, Redis, or similar databases.
• Experience using observability and log analysis platforms such as Splunk, Kibana, Grafana, Prometheus, or…