qa engineer (auto) in fintech

Astra Tech operates in the technology, information, and internet industry.

• 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.

• 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 such as Kafka and 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, with demonstrated ability to leverage LLM-based tools such as GitHub Copilot, Cursor, Claude Code, Codex, or similar;
• 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 spoken and written English;
• Nice to have: 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.

• No conditions specified