Senior, Software Engineer

Walmart Walmart · Retail · Sunnyvale, CA

Senior Software Engineer on the Mobile Performance Engineering team, responsible for building observability tools (MappWhiz) for Walmart's consumer-facing mobile applications. The role involves developing profiling components, implementing new profiling capabilities, integrating with mobile device tooling and cloud platforms, and contributing to the metrics pipeline. A key focus is exploring and contributing to Agentic AI features for automated root cause analysis and anomaly detection, layering LLM capabilities on top of collected profiling data.

What you'd actually do

  1. Develop and maintain core MappWhiz profiling components — including performance monitoring, session management, and profiling orchestration — ensuring high reliability and low overhead during automated test runs.
  2. Implement new profiling capabilities such as native heap dump analysis, UI trace collection (Perfetto / Instruments), call stack recording, and log correlation across Android and iOS platforms.
  3. Build and extend integrations with mobile device tooling (ADB for Android, Xcode Instruments / libimobiledevice for iOS) and cloud device platforms (Sauce Labs) for both local and cloud-based test execution.
  4. Contribute to test framework support across Appium, TestNG, JUnit, XCTest, and internal automation frameworks, making profiling instrumentation seamless for consuming teams on both platforms.
  5. Explore and contribute to Agentic AI features — such as LLM-assisted anomaly detection and intelligent performance recommendations — that layer on top of collected profiling data; prior exposure is a plus, but strong curiosity and willingness to learn are equally valued.

Skills

Required

  • Java or Python
  • Android and iOS mobile development and testing
  • mobile performance engineering and profiling
  • mobile test automation frameworks (Appium, Selenium WebDriver, TestNG, JUnit, or XCTest)
  • time-series databases (KairosDB, InfluxDB, or similar)
  • dashboarding/observability tools (Grafana, DataDog, or equivalent)
  • cloud device testing platforms (Sauce Labs, BrowserStack, or Firebase Test Lab)

Nice to have

  • Proficiency in both Java and Python
  • Agentic AI, LLMs, or AI-assisted developer tooling
  • LangChain, LangGraph, AutoGen, or CrewAI
  • native memory profiling tools
  • log aggregation platforms
  • Kotlin or Swift
  • 24x7 continuous testing infrastructure and CI/CD reliability practices
  • Strong written communication skills

What the JD emphasized

  • AI-driven performance analysis
  • Agentic AI capabilities
  • LLM-assisted anomaly detection
  • intelligent performance recommendations

Other signals

  • AI-driven performance analysis
  • Agentic AI capabilities
  • LLM-assisted anomaly detection
  • intelligent performance recommendations