I updated my workflow to use the AI_Job_Hunt_Agent_N8N file as the source of truth.
Instead of generating tailored resumes for every role, this version focuses on job-match intelligence:
- pull jobs
- compare JD vs resume profile
- score fit
- send ranked opportunities
Repo: https://github.com/parupati/AI_Job_Hunt_N8N
What the workflow does
Every day at 7:00 AM:
- Scrapes fresh jobs from SerpAPI (
google_jobs) for AI / Sr Full Stack Engineer - Loads a structured resume profile from a code node (summary, skills, experience, achievements)
- Sends each job description + resume profile to GPT-4o
- Parses AI response into structured fields like:
match_scorematch_tierapply_recommendation
- Sorts by score and selects the top 5 opportunities
- Sends a daily HTML email report with:
- company
- role
- location
- posting time
- match %
- tier
- recommendation
- job link
n8n node flow
- Schedule Trigger (daily at 7 AM)
- HTTP Request (SerpAPI jobs endpoint)
- Code: Load Resume Data
- Code: Prepare Jobs for Match Analysis
- OpenAI (GPT-4o) for JD-vs-resume fit analysis
- Code: Parse & Enrich Result
- IF + Code (filter/sort/top 5)
- Aggregate
- Gmail (send report)
Local setup
I run n8n with Docker:
services:
n8n:
image: n8nio/n8n:latest
ports:
- "5678:5678"
Start:
docker compose up -d
Open:
http://localhost:5678
Why this helped
The workflow doesnโt auto-apply to jobs.
It automates job triage so I can spend time only on high-fit opportunities.
This gave me:
- daily ranked shortlist instead of random browsing
- consistent JD-vs-resume evaluation
- faster decision-making on where to apply
Next improvements
- enforce score threshold directly in IF node
- add company blacklist/whitelist
- generate optional cover note for top matches
- send Slack + email notifications
If you want, I can share my importable AI_Job_Hunt_Agent_N8N.sanitized.json workflow and setup checklist.
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