IT Leader · AI Builder · US Air Force Veteran

Jason  Darrow

I don't just manage projects. I build them.
20 years delivering software. Recently back to hands-on
building, learning AI by doing. The results have been
surprising, even to me.

See the Projects GitHub → LinkedIn →
Background
20 Years in IT Delivery
Active Projects
2
Stack
Python · Claude API · Ollama · AWS
Status
Actively Building
Projects

AI Job Search System

What I Built

A job search tool I built for myself — and the first real AI project I have built and actually use. It surfaces relevant listings, gives me the company intelligence I need to decide whether to apply, and then handles the time-consuming parts: selecting the right resume bullets and drafting a cover letter. I stay in the loop at every step.

The pipeline scrapes job boards across multiple titles and locations, then I review each listing and mark the roles I want to pursue. For those roles, the system pulls company background, news, and a Claude-generated match score that compares the job description against my full 57-bullet resume database. I use that score to decide whether to move forward. When I do, Claude selects the best-fit bullets and drafts both a tailored resume and a voice-matched cover letter — both as editable Word documents I review and refine before anything goes out.

Python 3 Claude API Streamlit JSearch API (OpenWeb Ninja) NewsAPI DuckDuckGo python-docx pandas AWS S3 Git
View on GitHub →
# Launch the dashboard — runs the whole pipeline $ streamlit run dashboard.py ✓ Control panel live at localhost:8501 # ...or run each stage from the command line $ python3 job_scraper.py ✓ 42 jobs found · 18 passed filters ✓ Job descriptions captured for each posting ✓ Saved: job_listings.xlsx # Tailor resume to a specific role (JD auto-filled from Excel) $ python3 resume_tailor.py \ --company "Fidelity" \ --title "IT Delivery Manager" \ --description "..." ✓ Match score: 93 / 100 ✓ Bullets selected and summary rewritten # Generate submission-ready Word doc $ python3 resume_generator.py \ --input output/tailored_Fidelity.json ✓ Resume saved: Jason_Darrow_Resume_Fidelity.docx # Generate voice-matched cover letter $ python3 cover_letter_generator.py \ --company "Fidelity" \ --title "IT Delivery Manager" \ --description "..." ✓ Cover letter saved: CoverLetter_Fidelity.docx
Build Log — AI Job Search
0
Resume Database

Structured master resume in JSON — 57 bullets tagged by skill, strength scored, ready for AI selection.

Complete
1
Job Scraper

Config-driven job search via JSearch API (OpenWeb Ninja). Captures full job descriptions at scrape time. Filters by salary, recency, job type, and title allowlist. Outputs to dated Excel.

Complete
2
AI Resume Tailor

Claude API reads job description, selects best-fit bullets, rewrites summary, generates Word doc. 93/100 match score.

Complete
2.5
Company Intelligence

Enriches shortlisted roles with company background, recent news, and industry data via DuckDuckGo and NewsAPI. Claude API scores each role against the master resume (0–100 match) and displays the badge in the HTML report.

Complete
3
HTML Job Report

Generates a formatted HTML report of enriched listings with company briefs and one-click resume tailor commands.

Complete
4
Portfolio Site

This site — documenting the project, the journey, and the build. Hosted on AWS S3 with Route 53.

Complete
5
Streamlit Dashboard

Browser control panel for the whole pipeline. Each stage runs from a button with live logs; review and tailor without touching the terminal.

Complete
6
AI Cover Letter Generator

Claude API generates a voice-matched cover letter grounded in the same bullets selected for the tailored resume. Writing rules, anti-AI guardrails, and before/after examples embedded directly in the prompt. Outputs a submission-ready .docx.

Complete
7
Application Tracker

Notion API integration to track applications from submission through offer — synced from the pipeline automatically.

Planned
8
Expanded Search

Additional job source integrations for broader, fresher listings across more platforms.

Planned
Second Project

AI-Assisted GTD System

What I Built

A personal operating system powered by local AI — built to replace the external structure that employment provides. Leaving a 20-year career means losing standing meetings, a team, and an Outlook calendar as the heartbeat of the week. This project rebuilds that structure from the inside out.

The system runs a local LLM (llama3.1:8b via Ollama) on a Ubuntu machine, pulling open tasks from Notion and live events from Google Calendar to generate a focused morning briefing every day at 6:30 AM. No cloud dependency, no subscription cost — the model runs on a GTX 1080 in my home office. The briefing is delivered as a local HTML page viewable from any device on the network. Grounded in David Allen's GTD methodology and a Notion Ultimate Brain template.

Python 3 Ollama llama3.1:8b Google Calendar API Notion API GTD Ubuntu cron systemd
View on GitHub →
# Runs automatically at 6:30 AM via cron $ python3 morning_briefing.py ✓ Fetching tasks from Notion... 5 found ✓ Fetching calendar events... 2 found ✓ Briefing generated via llama3.1:8b (local GPU) ✓ Saved: morning_briefing.html # View from any device on the local network → http://linux-box:8088/morning_briefing.html
Build Log — AI-Assisted GTD
1
Foundation

Ollama + Open WebUI running locally on Ubuntu. Weekly planner prototype built as interactive HTML. Cursor Remote SSH connected. GitHub repo live.

Complete
2
Morning Briefing Agent

Python agent pulls live Notion tasks and Google Calendar events, generates a plain-English daily briefing via local LLM, delivers as HTML on the local network. Runs automatically every morning via cron.

Complete
3
Weekly Schedule Script

Agent pulls the week ahead from Google Calendar and Notion, generates a prioritized weekly plan with suggested time blocks.

Planned
4
Outlook-Style Weekly View

Visual, color-coded weekly planner populated from live Calendar and Notion data. Green for health, blue for deep work, purple for learning, amber for social, coral for admin.

Planned
5
Weekly Review Agent

Guides through GTD weekly review steps, surfaces stale projects and missing next actions, optionally writes suggested blocks to Google Calendar.

Planned
Background

About Me

I spent 20 years building and delivering software — starting as a web application architect at Bank of America, where I built systems responsible for billions in managed assets, and progressing to IT Delivery Manager at Voya Financial overseeing programs from $250K to $3M.

Instead of just sending resumes right away, I decided to build the tool I wished existed — an AI system that finds relevant jobs, tailors my resume to each one, and tracks my progress. This site documents that project, and the ones that followed.

I'm learning AI by doing, not watching. Every week something new gets built, committed to GitHub, and added to the system. The results have been genuinely surprising.

🎓
Education

MS Information Systems — Bentley College (Distinction)
BS MIS — Northeastern University (Magna Cum Laude)

📋
PMP · CSM Certified

Project Management Professional
Certified ScrumMaster

🛩️
US Air Force Veteran

Senior Airman
Honorable Discharge

🥋
BJJ Black Belt

Brazilian Jiu-Jitsu —
the hardest thing I've ever done

Get In Touch

Let's Talk

I'm currently open to IT Delivery Manager, Program Manager, and AI Operations roles in the Greater Boston area and remote.

If you're building something interesting with AI, or know someone who needs a delivery leader who can actually build — I'd love to hear from you.