Staff Development Engineer in Test - Android

PayPal PayPal · Fintech · San Jose, CA +1 · Software Engineering

This role focuses on architecting and implementing an AI-native test automation framework for Android, integrating AI-powered testing agents for test creation, triage, and bug analysis. It involves building tooling for developer productivity, enabling dynamic AI-driven test selection, and automating non-functional testing, with a strong emphasis on collaboration with ML engineers and platform teams.

What you'd actually do

  1. Architect and implement a robust test automation framework for native Android (Espresso or alternative)—prioritizing reliability, maintainability, and deep integration points for AI-powered testing agents.
  2. Collaborate with ML engineers and platform peers to co-design execution hooks and test data management systems enabling generative-AI-based test creation, triage, and bug analysis.
  3. Instrument test frameworks to capture rich, actionable data and signals, supporting both standard automation and AI-driven agents across the SDLC.
  4. Build, maintain, and scale tooling to enable fast, reliable, repeatable Android Functional, Integration, and end-to-end testing at every commit and release.
  5. Enable dynamic, AI-driven test selection, prioritization, and adaptive regression by integrating AI-generated test cases and selection logic into automation infrastructure.

Skills

Required

  • Android test automation (Espresso or alternative)
  • AI-powered testing agents
  • generative AI
  • test data management
  • CI/CD integration
  • performance benchmarking
  • memory profiling
  • security vulnerability scanning
  • UI regression testing
  • collaboration with ML engineers

Nice to have

  • iOS SDET collaboration
  • Harness CI/CD

What the JD emphasized

  • AI-powered testing agents
  • generative-AI-based test creation
  • AI-driven test selection
  • AI-native quality engineering

Other signals

  • AI-powered testing agents
  • generative-AI-based test creation
  • AI-driven test selection
  • AI-native quality engineering