Sr Software Engineer

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

Senior Software Engineer at PayPal focused on designing and implementing AI-driven testing architectures for mobile applications. This includes developing predictive test selection algorithms using ML, integrating AI/LLM capabilities for code generation and debugging via MCP servers, and creating AI-powered test optimization pipelines within CI/CD systems. The role also involves building comprehensive metrics collection infrastructure, a mobile mutation testing platform, and architecting a unified user provisioning system.

What you'd actually do

  1. Design and implement mobile Monorepo testing architecture utilizing NX build system, integrating CocoaPods dependency management, and establishing iOS-specific testing workflows to support scalable test execution across multiple mobile applications.
  2. Develop predictive test selection algorithms using machine learning techniques to analyze historical test data, code changes, and failure patterns, implementing these models within Harness CI to optimize test execution time by 40-60%.
  3. Architect unified user provisioning system by migrating disparate user creation mechanisms to a single-source conditioning platform, ensuring consistent test data management across all mobile testing environments.
  4. Build comprehensive metrics collection infrastructure to monitor mobile platform health, including custom instrumentation for tracking infrastructure issues, test flakiness rates, performance degradation, and resource utilization patterns.
  5. Design and implement mobile mutation testing platform using advanced code mutation techniques to validate test suite effectiveness, identifying gaps in test coverage and improving overall code quality metrics.

Skills

Required

  • Swift
  • SwiftUI
  • UIKit
  • Objective-C
  • XCTest
  • XCUITest
  • NX build system
  • CocoaPods
  • Machine Learning
  • CI/CD
  • Data Persistence
  • RESTful APIs
  • GraphQL
  • Asynchronous programming
  • Concurrency
  • MVC
  • MVVM
  • VIPER

Nice to have

  • SwiftData
  • Core Data
  • Combine framework
  • Swift Testing framework
  • Model Context Protocol (MCP)

What the JD emphasized

  • optimize test execution time by 40-60%
  • AI/LLM capabilities

Other signals

  • design and implement mobile Monorepo testing architecture
  • Develop predictive test selection algorithms using machine learning techniques
  • implementing these models within Harness CI to optimize test execution time by 40-60%
  • Integrate Model Context Protocol (MCP) servers into mobile development workflows by implementing MCP-compatible interfaces that enable engineers to leverage AI/LLM capabilities for automated code generation, test case creation, debugging assistance, and documentation generation
  • Create AI-powered test optimization pipelines within CI/CD systems