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Mid-level generalist QA role in Bangalore with broad skillset and brand recognition yields high applicant competition.
QA and backend testing skills transfer across industries, but AI/backend specialization raises domain specificity to medium.
Explicit 4-9 years plus mandatory automation, API, cloud, and backend testing skills imply high shortlisting strictness.
Lead backend architecture performance, scalability, and efficiency for AI-driven products.
Design and implement end-to-end test strategies including functional, integration, API, regression, and non-functional testing.
Drive continuous automation, CI/CD pipeline maintenance, and monitor production system quality metrics (drift, hallucination, retrieval).
Experience range: 4-9 years in software testing/engineering.
Strong expertise in STLC, Agile, test automation (Playwright/Selenium/Cypress), and programming in Python, Java, JavaScript, or TypeScript.
Hands-on knowledge with API and performance testing tools (Postman, REST Assured, JMeter, Gatling, k6).
Familiarity with microservices, distributed systems, cloud platforms (AWS/Azure/GCP), containerization (Docker/Kubernetes), and CI/CD pipelines.
Proven leadership in backend engineering with mentoring responsibilities in complex AI/ML system deployments.
Strong analytical skills to design risk-based test strategies aligned with system workflows and architectures.
Experience in integrating observability and monitoring tools (Grafana, CloudWatch, ELK) to maintain production quality and optimize system performance.