AI Agent / LLM Infrastructure Engineer building production agent systems across model routing, tool execution, cloud capacity, observability, and autonomous workflows.
I focus on systems where agents do real work: run tools, call models, manage cloud capacity, publish artifacts, and leave traces that can be debugged.
| Project | What It Proves | Stack |
|---|---|---|
| ai-shorts-matrix-pipeline | AI Shorts matrix pipeline: script, storyboard, AI video, FFmpeg polish, batch upload, multi-channel scheduling, and YPP-oriented cost tracking | Python, Typer, FFmpeg, Langfuse, YouTube Data API |
| agentic-chrome-fuzzing-harness | Agent-driven security testing harness: LLM-generated fuzz inputs, ASan feedback, tmux workers, crash capture, and dashboard | Chromium, ASan, Codex/Claude-style agents, Bash, Python |
| jobclaw | AI-powered job search agent: scrape jobs, match against a profile, draft applications, notify, and track outcomes | AI agents, Playwright, LLMs, automation |
| titan-builder-mcp | MCP server that lets AI agents interact with Ethereum builder / MEV infrastructure through tool calls | Rust, MCP, Ethereum |
- Agent pipelines: multi-stage workflows with retries, review points, typed artifacts, and traceable model calls.
- LLM infrastructure: model routing, quota/capacity planning, GPU/TPM operations, observability, and cost control.
- Automation tools: browser automation, publishing automation, job-search automation, and creator workflow tooling.
- Security-adjacent agent systems: long-running fuzzing/security-test harnesses and vulnerability intelligence workflows.
- Packaging public proof repos around agent infrastructure and creator automation.
- Turning private production work into clean open-source examples.
- Writing technical notes on Claude Code, Codex, MCP, model routing, and practical agent operations.
- Portfolio: https://zijiezhong.com
- LinkedIn: https://linkedin.com/in/j-z-57327b2b5