Software Engineer @ Google | MS in Computer Science @ NYU Courant 📍 Sunnyvale, CA | ✉️ xmeng975@gmail.com | 🔗 LinkedIn
I am a Software Engineer at Google working on large-scale AI agent infrastructure and full-stack systems within Google Ads. With an MS in Computer Science from NYU and experience spanning distributed systems, cloud computing, and generative AI, I focus on building highly scalable, low-latency backend architectures and intelligent workflows.
- 🚀 Currently focused on: Scalable backend infrastructure, agentic AI orchestration, and system optimization.
- 🛠️ Core Expertise: Distributed systems, cloud architecture (GCP/AWS), Kubernetes, and full-stack development.
- ⚡ Fun Fact: I love optimizing complex systems—whether it's cutting inference latency by 25% or fine-tuning infrastructure for heavy traffic.
June 2025 – Present | Mountain View, CA
- AI Agent Systems at Scale: Developed backend infrastructure for agentic AI systems serving over 1.2M daily active users, enabling scalable orchestration and execution of AI-driven workflows within Google Ads.
- Latency & Optimization: Implemented backend and inference optimizations that reduced end-to-end latency by 25%, significantly improving the responsiveness of AI-powered services.
- Full-Stack Ad Systems: Engineered full-stack solutions for the Google Ads platform supporting over 3M daily advertisers, building scalable user-facing features and internal tools with seamless AI integration.
- Interaction Caching: Enhanced interaction storage and caching mechanisms to optimize context reuse and retrieval efficiency for large-scale automation prompting pipelines.
July 2024 – Dec 2024
- Built and integrated a custom GenAI platform LLM with Retrieval-Augmented Generation (RAG), improving retrieval accuracy by 25%.
- Streamlined backend infrastructure using AWS S3 and RDS, boosting image generation feature engagement by 30%.
- Languages: Python, Java, C/C++, Go, JavaScript, TypeScript, Kotlin, C#, SQL
- Cloud & DevOps: Google Cloud Platform (GCP), AWS, Docker, Kubernetes, Tekton CI/CD, Linux
- Frameworks & Tools: Node.js, React.js, Vue.js, Django, Flask, Spring Boot, .NET Core, Git
- AI & Data Science: TensorFlow, PyTorch, Dialogflow, RAG Pipelines, Sentiment Analysis
- Ecommerce Web App A RESTful service built with Flask-RESTX and Swagger, featuring an automated CI/CD pipeline using Tekton for automated testing and deployment on Kubernetes.
- Handwritten OCR System A hybrid CNN-LSTM model built using TensorFlow and trained on the IAM dataset, achieving 95% accuracy across 5,000+ test images.
- CaptionMasterAI An Android application leveraging the Google Gemini LLM for social media caption generation, integrated with Firebase.
I'm always open to discussing distributed systems, generative AI infrastructure, or open-source collaborations. Feel free to reach out!
