About Me
AI Engineer passionate about building robust, human-aligned AI through the interplay of knowledge representation, retrieval-augmented generation, and agentic systems.
Background
I'm Zhiruo (Zoey) Zhang, a Master's graduate in Informatics from the University of Zurich, specializing in Data Science. I began my journey with a Bachelor's in Software Engineering, exploring NLP research through my thesis, and later deepened my expertise with advanced courses and projects during my Master's studies.
During my Master's, I conducted research in Knowledge Graph Question Answering (KGQA) as part of my thesis and then worked as a Research Assistant. I kicked off my industry experience at an AI startup, where I quickly proposed and prototyped the GraphRAG project, demonstrating initiative, research-to-application skills, and the ability to address real-world problems in industrial settings.
I also worked on an early-stage startup project with friends, where I handled the entire technical stack while participating in product positioning, fundraising preparation (business plan, investor outreach), market research, and beta testing guidance. Though we didn't formalize the company at pre-seed stage, this entrepreneurial experience taught me to balance technical excellence with business viability.
What I Do
🔍 RAG Engineering
Building production retrieval pipelines with measured quality. Systematic evaluation, reranking optimization, and honest reporting of what works and what doesn't.
🤖 Agent Architectures
Designing agent systems with intelligent routing, tool integration, and cost tracking. L0/L1/L2 classification to skip unnecessary LLM calls.
📊 Eval-Driven Development
Every feature measured: latency, recall, cost, accuracy. Building evaluation frameworks and keeping honest records of experimental results.
🚀 Full-Stack AI Products
End-to-end product development: FastAPI backends, Next.js frontends, Docker deployment, SSE streaming, and production monitoring.
🗄️ Data Processing & Governance
Structured data pipelines, ontology extraction, and knowledge graph construction. AI disclosure on health endpoints, prompt hash tracking, and transparent cost accounting.
⚙️ Scalability & Modularity
Service-oriented architecture with independent deployable components. Modular RAG services that can be consumed by multiple products without tight coupling.
Technical Skills
Programming Languages
Python, TypeScript, Java, SQL
AI / ML
RAG, LLMs, Agent Systems, Knowledge Graphs, NLP, Prompt Engineering, Model Distillation (ongoing), HPC Training & Deployment
Frameworks & Libraries
FastAPI, Next.js, React, PyTorch, LangGraph, Autogen
Databases & Knowledge Systems
PostgreSQL, Neo4j, pgvector, Chroma
Infrastructure & Cloud
Docker, Docker Compose, AWS (via Udacity certifications), HPC clusters, Git, Linux
Certifications & Continuous Learning
Completed Udacity Nanodegrees and courses to stay at the forefront of AI engineering:
Nanodegrees (10)
Courses (5)
Side Projects & Tools
Beyond core projects, I build tools to improve productivity and workflow:
📚 Chat Session Manager
Process downloaded chat session ZIPs into locally readable, queryable format. Supports embedding-based search and export to IntelliScribe for knowledge integration.
⚡ HPC CLI
Command-line tool for streamlined HPC cluster operations and job management.
📝 Quick Note Tool
Uninterrupted note-taking tool with video screenshots, text copy-paste, and AI Q&A capabilities (powered by llm-workflow modules).
AI Tools & Continuous Growth
I actively use and evaluate AI coding assistants to accelerate development:
I'm passionate about leveraging AI tools to grow with the field, while maintaining focus on experience accumulation — this combination helps me deliver products faster and with higher quality.
What I'm Looking For
I'm open to roles where I can:
- ✓Build production RAG systems and agent architectures at scale
- ✓Work on end-to-end GenAI applications — from experiment to deployment
- ✓Collaborate with teams that value measurement, honesty, and iteration
- ✓Continue growing in cloud infrastructure and enterprise AI deployment
Target roles: AI Engineer, RAG/Agent Specialist, Full-Stack + AI Engineer
Get in Touch
If my background and interests align with your team, I'd be delighted to discuss potential opportunities.