• Delivered a 3-hour battery life improvement over the modeled day of use on a Meta wearable product through

systematic power analysis and optimization across the full AOSP/Linux kernel/RTOS stack.

• Designed and implemented proxy metrics to detect power and thermal regressions during playtesting and field

deployment, keeping power/thermal issues below 1%.

• Deployed AI-powered code review tooling to audit firmware changes for power efficiency across both application and driver layers, enabling proactive identification of inefficient patterns before submission.

• Built and integrated MCP servers connecting AI assistants directly to Devices Under Test (DUT), enabling real-time querying of signal states and power rail data for deeper, context-aware firmware analysis.

• Designed and led company-wide power optimization training sessions for engineers across kernel, OS, RTOS, and application layers; produced archived video content to scale knowledge sharing across teams.

• Reviewed and provided sign-off on schematic changes for power and thermal design, ensuring hardware decisions align with product battery life and thermal budget requirements.

• Identified and delivered targeted power optimizations that enabled new feature launches on wearable products

while maintaining or improving day-of-use battery life.

• Defined repeatable power measurement procedures and tracked trends and regressions across firmware releases using power monitors, systrace, Perfetto, and Battery Historian.

• Performed low-level hardware debugging with logic analyzers, oscilloscopes, and JTAG to root-cause power

anomalies at the silicon and firmware level.

• Collaborated with hardware teams to integrate BOM components (spare GPIOs, power measurement ICs) enabling fine-grained power instrumentation and low-level debug capability.

• Reviewed architectural design documents for power efficiency; guided teams toward lower-power solutions before implementation.

• Mentored junior engineers and maintained internal wikis on embedded power debugging and optimization

techniques.

• Optimized power consumption on Meta's battery-powered RL products, contributing to measurable improvements in device day-of-use battery life.

• Profiled and optimized AOSP-based embedded devices across the full stack (apps, framework, Linux kernel, RTOS) using systrace, Perfetto, Battery Historian, logic analyzers, oscilloscopes, and JTAG.

• Reviewed architectural design documents and drove adoption of power-efficient implementation patterns.

• Developed and executed power measurement procedures for trend analysis and regression detection.

* Full stack research and development from dot net, to Angular and Cordova mobile apps.

* Creation and maintenance of containerized (Docker) dot net core api projects.

* Deployment to IIS on Windows Server.

* SQL Server migrations with TSQL and stored procedures.

* Cordova plug-in development for both iOS and Android platform.

* Esri ArcGis Server, JS, iOS and Android SDK integration.

* ArcPy development for higher level access to nodes and edges for navigation.

* Specialized turn by turn navigation with pathfinding algorithms.

* Coach and mentor junior developers on object oriented programming nuances and agile scrum practices.

* Develop the native apps written in Swift/Java with the mobile team.

* Seamlessly integrate with the backend to provide fluid user experience.

* Help improve code quality through writing unit tests, automation and performing code reviews.

* Use agile scrum methodology for product management.

* Design the software architecture.

* Integrate In App Purchases.

* Set up Universal and Dynamic links.

* Migrated to Kotlin for android.

* Started integrating RxSwift and using RXCocoa.