Senior, Software Engineer

About the role

The Mobile Performance Engineering team is responsible for building observability tools that give engineers deep, actionable insight into the runtime behavior of Walmart's consumer-facing mobile applications. MappWhiz is our in-house mobile profiling library — an instrumentation engine that integrates directly into automated test pipelines to continuously monitor CPU consumption, memory pressure, battery drain, call stacks, and UI jank across real and cloud-hosted Android and iOS devices. Our mission is to give every mobile engineer at Walmart the ability to detect and eliminate regressions before they reach customers at scale, and to push that mission further with intelligent, AI-driven performance analysis.

What you'll do

• 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.
• 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.
• 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.
• Contribute to test framework support across Appium, TestNG, JUnit, XCTest, and internal automation frameworks, making profiling instrumentation seamless for consuming teams on both platforms.
• Contribute to and extend the metrics pipeline — including KairosDB time-series data models and Grafana dashboards — ensuring metrics are accurately tagged by device, OS platform, app version, scenario, and iteration.
• Work on the reporting and analysis layer, helping deliver actionable regression detection and performance optimization recommendations via HTML reports and notification pipelines (Slack, email).
• 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.
• Participate actively in code reviews, contribute to engineering standards, and support junior engineers through pair programming and knowledge sharing.
• Partner with Android and iOS app teams to onboard them onto MappWhiz, gather their profiling requirements, and help translate them into library improvements.
• Support CI/CD pipeline integration to run continuous performance profiling on every build, enabling proactive detection of performance regressions before production release.

Requirements

• Bachelor's degree or higher in Computer Science, Software Engineering, or equivalent professional experience.
• 4–7 years of software engineering experience, with demonstrated strength in Java or Python (proficiency in either is required; familiarity with both is a plus).
• Fair understanding of Android and iOS mobile development and testing — including platform-specific build systems, debugging tools, and device management workflows (ADB, Xcode, Simulator/Emulator).
• Experience with or genuine interest in mobile performance engineering and profiling — including CPU, memory, battery, and UI rendering analysis; candidates actively growing into this specialization are encouraged to apply.
• Working knowledge of mobile test automation frameworks such as Appium, Selenium WebDriver, TestNG, JUnit, or XCTest.
• Familiarity with time-series databases (KairosDB, InfluxDB, or similar) and dashboarding/observability tools (Grafana, DataDog, or equivalent).
• Familiarity with cloud device testing platforms such as Sauce Labs, BrowserStack, or Firebase Test Lab.
• A demonstrated appetite for learning new technologies quickly and adapting to new environments — someone who gets energized by evolving toolchains and greenfield problems.

Qualifications

• Preferred Qualifications:
• Proficiency in both Java and Python.
• Exposure to or interest in Agentic AI, LLMs, or AI-assisted developer tooling — hands-on experience with frameworks such as LangChain, LangGraph, AutoGen, or CrewAI is a strong differentiator.
• Experience with native memory profiling tools such as Android Memory Profiler, Heaptrack, Xcode Instruments Memory Graph, or MAT.
• Familiarity with log aggregation platforms (OpenObserve, OpenTelemetry, ELK stack).
• Knowledge of Kotlin or Swift for deeper collaboration with mobile app engineering teams.
• Experience with 24x7 continuous testing infrastructure and CI/CD reliability practices.
• Strong written communication skills for technical documentation, runbooks, and onboarding guides.

Benefits

Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include : Stock