A technology attorney who builds the AI he governs — and who ran the enterprise systems AI now sits on top of. Most AI-governance people have one of those legs; I have the triangle. I design and ship secure, citation-grounded LLM systems and own the legal, privacy, and risk frameworks that keep them defensible. Spokane, WA · open to remote / relocation / international.
- ⚖️ Practicing attorney (WA Bar, 2010) — technology, IP, privacy (HIPAA/GDPR), cyberlaw
- 🏛️ AI governance — NIST AI RMF, EU AI Act, model risk & audit; IAPP AIGP (certified 2026, No. 192392076)
- 🛠️ Hands-on builder — local-first RAG, anti-hallucination verification, evaluation harnesses
- 📊 Enterprise data & cloud architect (Nike, Costco) — the systems AI now runs on
- 🎤 Authored & taught a WSBA-accredited CLE on the ethical use of LLMs in law (2025)
wa-legal-ai-showcase — Air-gapped legal-research AI for Washington State law (public showcase of the architecture; the production system, corpus, and prompts are private).
A 7-stage retrieval pipeline (rewrite → retrieve → rerank → pack → answer → verify → render)
over 428K legal authorities that refuses to hallucinate: every citation is verified against the
corpus before it reaches the user. On a 150-question attorney-reviewed gold set it scores
98%+ citation accuracy with zero hallucinations, fully on-prem — the kind of control a
Head-of-AI-Risk has to specify and be able to verify.
Python · FastAPI · PostgreSQL/pgvector · Ollama · Claude · Docker
wa-cite-check — Catches the mistake getting lawyers sanctioned.
Point it at a motion (.docx/.pdf) and it flags every fabricated, mis-named, or wrong-year citation,
plus authorities that have been overruled or repealed — fully offline. An optional LLM judge checks
whether each cited authority actually supports the proposition it's cited for.
Python · SQLite · click · LLM-as-judge
muni-bond-ai-showcase — The same anti-hallucination architecture, re-pointed at federal tax-exempt municipal bond law (IRC, Treasury Regs, IRS guidance, Tax Court).
On a 12-question attorney-authored gold set: zero invented citations, 98.9% claim-to-evidence
coverage, 100% out-of-domain refusal — proof the methodology is a reusable platform across
regulated domains, not a one-off.
Python · FastAPI · PostgreSQL/pgvector · local LLMs (vLLM/llama.cpp) · Claude
complyguard-showcase — Compliance-by-design, automated.
Crawls an e-commerce site and audits it against state + federal consumer-protection law across all 52 US jurisdictions —
a 71-rule engine plus a Claude analysis pipeline that returns risk scores, statutory citations, and
plain-English fixes. A full-stack product, not a demo: authentication, Stripe billing, background jobs, PDF/DOCX reports.
Next.js · TypeScript · PostgreSQL/Prisma · Stripe · Playwright · Claude
Python · Claude · Ollama (Llama / Mistral / DeepSeek / Qwen) · pgvector · FastAPI ·
Docker · AWS & on-prem/local · RAG · evaluation & guardrails · model fine-tuning
AI governance sits where legal risk, enterprise systems, and real deployment meet — I'm not changing careers, these threads converged. I'm looking to own an organization's AI-governance program end to end as an operating leader (AI governance, responsible-AI engineering, or trustworthy AI in a regulated domain), and I take on fractional / interim Chief-AI-Risk engagements.