Position: Senior QA Engineer – Backend Services, Automation & Performance Testing

Key Responsibilities

· Design, implement, and execute comprehensive test strategies for backend services, covering functional, integration, automation, and performance testing.

· Validate complex backend business workflows across distributed microservices, ensuring system reliability, data consistency, and service stability.

· Develop and maintain scalable automation frameworks for API, integration, and database validation to support CI/CD pipelines.

· Design and execute performance, load, stress, and endurance testing to evaluate system scalability, stability, and capacity under high transaction volumes.

· Analyze performance bottlenecks using logs, metrics, distributed tracing, thread dumps, and database profiling, and provide optimization recommendations.

· Validate data consistency and transaction integrity across databases, message queues, and downstream services.

· Debug complex backend issues involving asynchronous processing, distributed transactions, and event-driven architectures.

· Leverage AI-assisted software engineering tools to improve test design, automation development, defect analysis, root cause analysis, and overall engineering productivity.

· Collaborate closely with engineering, product, DevOps, and architecture teams to ensure high-quality delivery of backend services.

Required Qualifications

· Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

· 5+ years of QA experience focusing on backend services, distributed systems, or large-scale enterprise applications.

· Strong hands-on experience in API automation, integration testing, database validation, and end-to-end backend testing.

· Solid experience with performance testing tools such as JMeter, k6, Gatling, or equivalent.

· Strong understanding of distributed microservices, REST APIs, asynchronous messaging systems (e.g., Kafka, RabbitMQ), and event-driven architectures.

· Experience analyzing performance bottlenecks using monitoring platforms, distributed tracing, application logs, and database profiling.

· Strong SQL skills with experience validating data consistency across multiple systems.

· Proficiency in at least one programming language such as Java or Python.

· AI-assisted software engineering experience is required, with demonstrated ability to leverage LLM-based tools (e.g., GitHub Copilot, Cursor, Claude Code, Codex, or similar) to improve testing efficiency, automation development, debugging, and root cause analysis.

· Hands-on experience applying AI to software testing, including AI-assisted test case generation, automation development, intelligent defect analysis, or test workflow optimization.

· Excellent debugging, troubleshooting, and root cause analysis skills for complex backend systems.

· Experience with CI/CD pipelines and modern software development practices.

· Fluent in spoken and written English.

Preferred Qualifications

· Experience in fintech, banking, payment, lending, or other transaction-intensive systems.

· Experience testing high-concurrency and high-availability backend services.

· Familiarity with cloud-native technologies and observability tools such as Docker, Kubernetes, Prometheus, Grafana, ELK, or Jaeger.