Emmanuel Katipunan

Key Responsibilities & Achievements:

• End-to-End AI System Architecture: Designed, developed, and deployed production-ready AI systems, including an Inbound AI Voice Agent that handles real-time inquiries and appointment setting via WebSockets and LLM function calling.
• Scalable AI Pipelines: Built and maintained robust data pipelines in Laravel and Python to process thousands of records for the AI Mail Blaster, generating 1k+ hyper-personalized outbound messages per batch using Gemini and OpenAI.
• NLP & Automated Intelligence: Developed an enterprise Call Transcription & Summarization engine using OpenAI Whisper and Pydantic to extract structured qualifying data from raw audio, automating lead scoring and CRM synchronization.
• Feature Engineering & Data Research: Engineered an Autonomous ICP Engine that performs web-scraping and data-cleaning to transform unstructured company data into structured Ideal Customer Profiles using LangChain and Vector Databases.
• Model Optimization & Performance: Optimized LLM token usage and latency for real-time voice applications, ensuring sub-500ms response times for a seamless user experience.
• Data-Driven Decision Making: Developed a Campaign Insights AI to perform predictive analysis on historical campaign data, identifying conversion drop-offs and success patterns to guide marketing strategy.
• Cloud Infrastructure Management: Managed the deployment of AI workloads on GCP (Cloud Run) and AWS (EC2/S3), ensuring scalable infrastructure and compliance with data privacy standards.
• Cross-Functional Collaboration: Collaborated closely with the sales and data teams to integrate AI-driven features into the live Callbox ecosystem, ensuring technical specifications aligned with business goals.