John Doe
AI/LLM Delivery & Governance Leader

Executive Summary

Delivery leader focused on turning AI/LLM capability into auditable, repeatable outcomes through governance, operating models, and disciplined execution.

Core Strengths

AI/ML
LLM workflow design, Prompting & evaluation, Human-in-the-loop patterns, Model risk awareness, NIST AI RMF literacy
Product
Narrative writing, Decision-grade synthesis, Stakeholder alignment, Metrics, Executive packaging
Engineering
Python, YAML-first authoring, Jinja templating, CLI tooling, Git workflows, Markdown-first artifacts
Leadership
Program governance, Operating model design, Change enablement, Delivery discipline, Risk/compliance communication

Signature Proof (Projects)

CVFoundry-Lite
Built a self-contained resume generator from canonical YAML + config YAML using Python + Jinja, optimized for portability (single HTML file).
CVFoundry (Concept)
Developed a pragmatic approach to “CV as code”: structured data + templates + deterministic builds instead of manual Word/PDF version sprawl.
KOS / TRACE (Concept)
Explored a tool-neutral control-plane for Human–AI co-collaboration where thinking becomes durable artifacts.
ResDoc Template + Shared Engines
Created a Markdown-first, Git-friendly scaffold for AI-assisted research and decision-support deliverables (TRACE loop + TILETS staging).

Selected Experience

Role Company Dates Impact
AI Transformation & Governance Lead
Global Consulting Firm Oct 2025–Present Authored an AI strategic plan with a Crawl–Walk–Run maturity model aligned to NIST AI RMF and practical delivery constraints.
Builder — Intent-to-Artifact Workflows
Self-Directed (Open Work) Oct 2025–Present Designed and implemented an “Intent Foundry” approach: staged human–AI collaboration that turns ambiguous intent into tempered, traceable, execution-ready artifacts.
Senior Product Manager
Acme Software Jan 2019–May 2022 Owned roadmap for a workflow automation platform; grew active users 3x and improved retention by 18%.