I'm a Senior Software Engineer at Twilio, working on cutting-edge AI Assistants technology. With a strong background in building scalable, production-grade systems, I'm passionate about creating innovative solutions that make a real impact.

• 🔭 Currently working on AI Assistants at Twilio
• 🌟 Previously built Twilio Engage features at Segment, including mobile push notifications and analytics
• 💡 Experienced in full-stack development, distributed systems, and customer engagement platforms
• 🎯 Focused on delivering high-quality, maintainable code

Current

Building next-generation AI Assistants platform

• 🤖 Developing conversational AI capabilities powered by large language models
• 🏗️ Architecting scalable backend systems to handle real-time AI interactions
• 🔌 Integrating AI/ML models into production with low-latency requirements
• ⚡ Building APIs and SDKs for seamless integration with Twilio's communication platform
• 🎯 Optimizing performance and reliability for enterprise-grade AI solutions

Previous Role

Contributed to Twilio Engage - a leading customer engagement platform

• 📱 Built Mobile Push Notifications features enabling personalized messaging campaigns across iOS and Android platforms
• 📊 Developed Analytics and data visualization tools to help businesses track campaign performance and user engagement metrics
• 🏗️ Architected Organization and Permission Systems to manage multi-team workspaces with role-based access control
• ⚡ Optimized performance for high-throughput data processing, handling millions of events per second
• 🔧 Implemented features for audience segmentation, journey orchestration, and real-time personalization

Previous Role

Worked on Autopilot - an AI-powered SEO platform

• 🤖 Implemented intelligent automation features for AI-driven content recommendations and SEO optimization workflows
• 🔧 Built tools for content optimization enabling marketers to improve organic search performance and rankings
• 📊 Developed data processing pipelines to analyze website performance metrics and competitor insights
• 🏗️ Enhanced platform scalability and reliability to support enterprise-level SEO operations
• ⚡ Integrated machine learning models for predictive analytics and automated decision-making in digital marketing

• Fine-Tune & Deploy LLMs with QLoRA on Sagemaker + Streamlit - Udemy (Oct 2025)
  • Skills: Large Language Models (LLM), AWS SageMaker, PyTorch, TensorFlow
• The Complete Agentic AI Engineering Course (2025) - Udemy (Oct 2025)
  • Skills: Large Language Models (LLM), Agents, OpenAI API, Python
• LLMs with Google Cloud and Python - Udemy (Dec 2023)
  • Skills: Large Language Models (LLM), Python, Google Cloud Platform (GCP), Pandas, Jupyter

• Next.js 14 & React - The Complete Guide - Udemy (Jan 2024)
  • Skills: React.js, Next.js, CSS, JavaScript, HTML, MongoDB
• CSS - The Complete Guide 2024 - Udemy (Mar 2023)
  • Skills: SASS, CSS, Cascading Style Sheets, Web Applications
• GraphQL with React: The Complete Developers Guide - Udemy (Jan 2022)
  • Skills: GraphQL

• Complete Guide to Protocol Buffers 3 [Java, Golang, Python] - Udemy (Aug 2024)
  • Skills: Protocol Buffers
• Pydantic V2: Essentials - Udemy (Jul 2024)
• Go Design Patterns - LinkedIn (Apr 2022)
  • Skills: Go (Programming Language)
• Learning the Go Standard Library - LinkedIn (Apr 2022)
  • Skills: Go (Programming Language)

• Learn DevOps: Infrastructure Automation With Terraform - Udemy (Apr 2023)
  • Skills: Terraform, Amazon Web Services (AWS)
• Datadog: Performance monitoring tool (from Zero to Hero) - Udemy (May 2022)
  • Skills: Datadog
• Git & GitHub - The Practical Guide - Udemy (Jun 2023)
• YAML Zero to Master - Udemy (Mar 2023)
  • Skills: YAML, Terraform

1. Detecting Community Structure Based on Optimized Modularity by Genetic Algorithm in Resting-State fMRI

   • Springer, Cham - May 2017
   • Research on detecting community structure of brain networks using rs-fMRI data to determine differences between autism spectrum disorders (ASDs) and normal controls. Proposes GAcut method using genetic algorithm to automatically detect community structure based on optimized modularity Q.

2. Uncovering Community Structure in Neuronal Functional Networks from Multi-neuronal Spike Trains

   • Springer, Singapore - January 2016
   • Proposes a neuronal functional network community structure detection method using random walk distance and spectral decomposition to automatically determine the number and structure of neuronal functional networks.

3. Partitioning the Firing Patterns of Spike Trains by Community Modularity

   • CogSci 2015 - July 2015
   • Novel approach to analyze groups of firing patterns of neuronal spike trains based on community structure partitioning and modularity function Q, enabling automatic identification of optimal number of groups in neuronal firing patterns.

• 💻 Building production-grade AI systems at Twilio
• 🚀 Contributed to Twilio Engage, a platform used by thousands of companies
• 📱 Developed mobile engagement features serving millions of users
• 🔧 Experience with high-scale distributed systems
• 🌟 Passionate about clean code, system design, and best practices