Applied AI Engineer
Tony Trieu
I build AI agents that plug into the tools enterprise IT teams already use with approval workflows so nothing happens without the right sign-off and keep them running in production.
About
Who I Am
Computer Engineering grad from UC Riverside, Dean's Honor List.
I got into AI engineering because I wanted to build things that people can actually rely on.
- AI Systems
- AI agents, agentic workflows, RAG, context engineering, model evaluation
- Backend
- Python, FastAPI, PostgreSQL, pgvector, REST APIs, Ray Serve
- Cloud
- GCP, Docker, Supabase, Neon, Render
- Languages
- Python, TypeScript, C++, CUDA C
- AI Models
- Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 3.0 Flash
Experience
Where I've Worked
Chinchill.ai
CurrentApplied AI Engineer
March 2026 – June 2026
- · Started as an intern, shipped a production Jira integration on day one, and was promoted to full-time engineer after my first week
- · Connected the meta-agent to Jira, JSM, ServiceNow, Freshservice, and Confluence so it could perform agentic IT operations
- · Extended the messaging layer to Slack, Teams, Google Chat, and GitHub so employees get help without leaving the tools they're already in
- · Built the memory and knowledge layer so agents find the right answer from internal docs instead of guessing, and remember context across conversations
- · Engineered HITL guardrails so agents never take action without the right person signing off first
- · Diagnosed and fixed production failures across the deployment layer, authentication, and enterprise connectors
Python · FastAPI · Pydantic AI · PostgreSQL · Ray Serve · Gemini · GCP
Projects
What I've Built
March 2025 – Present
ScheduleBud
Lead Applied AI Engineer
An AI scheduling app that automates academic scheduling for college students
- · Students tell it what they need in plain English and it builds a schedule around their needs.
- · Every answer comes from real course data. The AI doesn't get to guess
- · Each student's data is isolated at the database level, independent of anything happening in the application code
- · Simple questions route to cheaper models, while complex ones route to more capable ones.
TypeScript · Node.js · Supabase · Gemini · PostgreSQL
Spring 2025
QKV Attention Acceleration
CS 147 Final Project
A final project about GPU kernel optimization for the attention operation at the core of every large language model
- · Dug into how memory access, parallelism, and compute bottlenecks interact in GPU kernels, the same tradeoffs that show up in production AI inference at scale
CUDA C · GPU Architecture
Contact
Let's Talk
I'm open to full-time Applied AI Engineering roles. If you're building something with AI agents, enterprise integrations, or AI infrastructure, I wanna learn more about it.
tonytrieu.dev@gmail.com