AI Engineer | Python, FastAPI, LLM applications, agents, and evaluation
I build LLM applications, agents, and evals for contract AI engineering. The named paid engagement is Acuity Real Estate. Other public repos below are independent portfolio work unless a line says paid.
Portfolio · LinkedIn · Acuity SMS bots · DocExtract
| Project | Evidence | Context |
|---|---|---|
| Acuity SMS bots | Client-reported 500+ inbound leads during a January to March 2026 deployment; 1,700+ tests at handoff; audit of 226 existing GHL workflows | Paid engagement |
| DocExtract | 95.5% weighted field-level accuracy on 28 committed offline replay fixtures; separate 202-case authoring corpus; 80% CI coverage gate | Independent engineering |
The two hero repositories above hold the primary evidence. This small index makes their release-gate, action-boundary, retrieval-failure, and client-scoping patterns runnable without an API key:
git clone https://github.com/ChunkyTortoise/llm-reviewer-path
cd llm-reviewer-path
uv sync --group dev
uv run pytest- chatbot-widget - multi-tenant chat widget (historical learning project — see its banner; current work starts at llm-reviewer-path)
- ai-workflow-api - YAML-driven workflow API
- Eval-driven multi-model runs: personal developer infrastructure for one-writer / independent-gate coordination. Not a product.
Strongest: AI Engineer, Applied AI Engineer, AI Backend Engineer, selective Forward Deployed Engineer.
Not targeting: Senior/Staff/Principal/Lead titles, research-scientist roles, model-training-heavy ML roles, QA-only roles.