Developed the Network Planner Assessment Tool using OpenAI to automatically evaluate regional and parcel impact scenarios, cutting review time from hours to minutes. 

Engineered real-time synchronization between SOM (Signal Order Management) and RPS across 50+ order types, reducing order proposal workflows by 75% and eliminating system-switching for planners. 

Delivered core components of the OneMDM → RPS migration by implementing metro-specific business rules, context-aware UI behaviors, and fault-tolerant data integration. 

Redesigned the RND Layout Engine, decoupling rendering components and resolving long-standing layout failures impacting 50+ planners. 

Led the EV2 migration for RPS Order Management, removing all S360 security blockers, enforcing modern TLS compliance, and restoring deployment velocity. 

Developed reliable multi-region data synchronization pathways across SOM, CSPW, and RPS, reducing data integrity issues across planning workflows.

Created an AI Insights Python framework for mobile network testing, analyzing logs, time-series data, call model traces, and performing anomaly detection & core dump analysis. Utilized sentiment analysis and GPT4 for log analysis, working closely with Microsoft Research, drastically reducing bug detection and RCA time from 2 hours to 5 minutes.

Developed auto-ticketing and duplicate incident tracking system using OpenAI LLMs and sentence embeddings, enabling automatic RCA identification and resolution for new incidents, enhancing issue detection for major customers such as AT&T, Etisalat, 3UK, decreasing incident time and contributed to a projected $4.6 million in savings.

Developed end-to-end smoke, soak, and resiliency Python test suites via Azure DevOps Pipelines, adopted by over 5 teams, achieving a 95% reduction in manual testing hours and saving approximately 110 hours monthly

Led major infrastructure development and architecture refactors in Azure, deploying multiple production-grade Kubernetes clusters with Azure Key Vault, Application Gateway, enhancing security and deployment efficiency.

Conducted Azure GPT training for 143 developers, contributed to multiple AI-related patents, authored a white paper on Iterative Testing, and led tech sessions on AI and Machine Learning fundamentals.

Patents Filed: AI-BASED ROOT CAUSE ANALYSIS FOR TELECOMMUNICATIONS SYSTEMS & SMART PROMPT GENERATOR FOR GPT MODELS

Lead developer on identity access management microservice used to authenticate users for a major CVS Health client

Developed additions to existing automated testing application to support next generation authentication methods

Worked closely with system architecture team to integrate performance optimizations into end-to-end systems

Mentor and leader for several members onboarding onto the team, providing in-depth knowledge transfers to peers

Created, trained, and tested one of two machine learning models that is used to provide venue occupancy counts

Refactored video analytics codebase and made improvements that greatly reduced false positive and error rates