I help teams run reliable, developer-facing platforms by owning high-severity investigations, designing scalable triage + escalation workflows, and translating support insights into documentation and automation.
I'm a senior support professional with 5+ years of experience supporting complex SaaS products and high-touch enterprise customers. I'm systems-minded, calm in ambiguity, and drawn to the "hard" problems: the ones that need careful investigation, crisp communication, and strong cross-functional execution.
My focus is building support that scales: structured triage, clear escalation paths, operational signals (patterns + trends), and documentation that turns one-off fixes into repeatable solutions.
I'm especially interested in support models where AI enhances human expertise by using structured workflows, better context capture, and automation to reduce friction while keeping a high-touch path for complex cases.
I've been experimenting with conversational AI patterns via my Dialogflow portfolio assistant (the chatbot below), applying support engineering principles: intent handling, contextual responses, and graceful fallback logic.
I'm drawn to companies building critical internet infrastructure and developer platforms where support excellence directly impacts millions of end users and the developers building on top of these platforms.
Problem
How can I demonstrate conversational AI design while making it easy for recruiters to explore my background interactively?
Approach
Built a Dialogflow-powered chatbot trained on my skills, experience, and career focus. It answers questions about my technical expertise, projects, and what I'm looking for by applying support engineering principles like clear intent handling, contextual routing, and fallback logic.
Outcome
Created an interactive way for visitors to learn about my experience while demonstrating how I approach conversational AI design: structured flows, empathetic responses, and documentation-led answers.