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Job Closed

Walk-in || Software Test Engineer

  • Source: Naukri
  • Neurealm
  • $5,266.48 to $15,799.45 /yr
  • On-site
  • Bengaluru
  • Full-Time
  • Mid level

Job Description

Preferred Immediate Joiners only

This interview primarily focused on QA fundamentals, Automation (Selenium/Python), API testing, Database/Unix, AI-assisted testing, Performance & Security testing, and real-world troubleshooting scenarios

QA & Automation

  • QA experience, project overview
  • Selenium, Playwright, Python, PyTest, Robot Framework
  • Framework design, POM, waits, stale element handling

Testing Fundamentals

  • STLC phases
  • Functional test coverage measurement
  • RCA for production defects
  • Smoke vs Sanity vs Functional vs Regression testing
  • Different testing types (Integration, Performance, Security, UAT, etc.)

Performance & Security

  • Load, Stress, Endurance testing
  • Capacity planning and hardware sizing
  • Security testing basics (Auth, Authorization, SQL Injection, XSS)
  • Security validation in lower environments

AI in Testing

  • Using AI for test case generation and automation
  • Measuring coverage of AI-generated tests
  • Prompt engineering and context setting
  • Risks and governance of AI usage

File Transfer Testing Scenario

  • Positive, negative, and boundary test cases
  • Maximum Concurrency validation
  • Stability Seconds validation
  • Concurrent file transfer testing
  • Automation approach using Python/PyTest/Boto3

API & UI Testing

  • API vs UI validation strategy
  • Response validation beyond status codes
  • PUT vs PATCH
  • Authentication handling
  • Contract testing
  • Troubleshooting environment-specific API failures

Database & Unix

  • Linux/Unix commands and log monitoring
  • Port validation
  • Database backup concepts
  • TRUNCATE vs DROP
  • pg_dump vs pg_basebackup
  • Data reconciliation and investigation techniques

Python Concepts

  • List, Tuple, Set, Dictionary usage
  • Shallow vs Deep Copy
  • Generators
  • Exception handling
  • SQL injection prevention
  • Efficient validation of large datasets

Troubleshooting Scenarios

  • Missing UI data (Database vs UI issue)
  • Date-filtered reports returning incorrect results
  • Production defect investigation and prevention
  • Intermittent automation test failures

Skills

  • selenium
  • Python
  • Playwright
  • Pytest
  • robot-frame-work
  • sanity_2
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