Resume as Code

This repository treats my professional career documentation as a software product. Instead of manually editing Word documents, this project uses a Zero-Touch CI/CD pipeline to compile my resume from clean Markdown source, inject real-time data, and enforce strict governance on PII and formatting.

📐 Architecture & Pipeline

Every commit to src/ triggers a GitHub Actions workflow that executes the following "Source to Distribution" pipeline:

graph TD
    subgraph Import ["Legacy Import (Local)"]
        Docx["imports/*.docx"] --> ImportScript["npm run import"]
        ImportScript --> Detect["Detect Title & Body"]
        Detect --> InjectFM["Inject Frontmatter"]
        InjectFM --> Sanitize["Sanitize PII"]
        Sanitize --> Src["src/*.md"]
    end

    subgraph Input ["Source Layer"]
        Src --> Config["resume.config.json"]
        Config --> Vars["GitHub Variables<br/>(Title, Name, Links)"]
        Config --> Secrets["GitHub Secrets<br/>(Phone, Email)"]
    end

    subgraph Build ["Assembly Layer"]
        Src --> Assemble["npm run build / assemble.js"]
        Vars --> Assemble
        Secrets --> Assemble
        Assemble --> Header["Inject Golden Header"]
        Header --> Replace["Replace Variables"]
    end

    subgraph Output ["Distribution Layer"]
        Replace --> Dist["dist/*.md"]
        Dist --> PDF["pdf/*.pdf"]
        Dist --> Safe["markdown/*.md<br/>(Safe Mode / Web)"]
    end

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Pipeline Stages

1. Legacy Import: The npm run import command converts local .docx files, intelligently detects job titles, and generates clean Markdown with YAML Frontmatter.
2. Source Separation: The pipeline separates Source Code (src/) from Distribution Artifacts (dist/ and pdf/).
3. Governance & Assembly: The assemble.js engine reads resume.config.json and Frontmatter to determine the correct Job Title, then injects the "Golden Header" at runtime.
4. PII Injection: Contact details (Phone, Email) are injected from GitHub Secrets only during the build process, ensuring they never appear in the source history.
5. Compilation: Converts the processed Markdown into print-ready PDFs with embedded metadata using Pandoc and XeLaTeX.

🎯 Key Features

Security-First Architecture

• PII Decoupling: Personal contact information is stored in GitHub Secrets (masked in logs), while configuration is stored in Variables.
• Bot-Resistant: Contact details only appear in compiled PDFs, not in plain-text source files.
• Safe Web View: The markdown/ folder contains "Safe Mode" resumes (redacted PII) for public web hosting.

Automated Governance

• Docs-as-Code: Resumes are defined with YAML Frontmatter (title: Platform Engineer), allowing for infinite variants from a single pipeline.
• Standardized Identity: A "Golden Header" template ensures consistent branding across all PDF outputs, regardless of the source file format.
• Idempotency: The pipeline guarantees consistent output regardless of execution count.

🛠 Tech Stack

• Core: Markdown, Pandoc, XeLaTeX
• Scripting: Node.js (Automation & API interaction)
• Diagrams: Mermaid.js (via Puppeteer)
• CI/CD: GitHub Actions
• Fonts: Liberation Serif & Sans (cross-platform compatibility)

📂 Project Structure

resume-as-code/
├── src/                   # <--- SOURCE OF TRUTH: Clean Markdown with Frontmatter
│   ├── RyanBumstead_Resume.md
│   └── RyanBumstead_PlatformEngineer.md
├── imports/               # <--- DROP BOX: Place .docx here for conversion
├── scripts/               # Node.js automation logic
│   ├── assemble.js        # Template engine & Header injection
│   ├── import-local.js    # Docx conversion & Title detection
│   ├── build.js           # Local build orchestrator
│   └── update-stats.js    # GitHub API data fetching
├── resume.config.json     # Configuration for Resume Variants
└── package.json           # Project Manifest & Command definitions