👻 ghostssh — Autonomous Job Hunting Agent

AI Job Search Agent for Engineers & Developers

GhostSSH analyzes your GitHub projects, LinkedIn history, and personal portfolio data. Then, our autonomous ReAct reasoning agent hunts and matches roles specifically to your technical evidence.

Optimal forAI EngineersML EngineersGenAI DevelopersData & MLOps

🔮 Autonomous Job Search Agent

Configure your hunt pipeline below. Let the agent parse your profile evidence, search live feeds, and rank roles.

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Step 1: Add Your Profile Context

We extract repository technologies, project descriptions, star counts, and coding patterns directly.

Add Profile URLs (GitHub, LinkedIn, Personal Site)

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Step 2: Define Job Hunting Targets

High values search wider but increase LLM scoring execution time.
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Step 3: Choose LLM Orchestration Mode

🚀 **Zero Token Configuration Required:** Running via high-speed pre-allocated server inference (Groq Llama 3 model). Free and unlimited search capability active.
🔒 **Privacy & Safety Disclosure:** Your profile context details are utilized strictly to score and map job alignments. API keys, if provided via BYOK mode, are held ephemeral client-side, sent strictly directly to the respective model API endpoint providers, and **never** stored or cached on our databases.
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Step 4: Launch Job Hunt

Asynchronous background worker logs step-by-step reasoning maps, searches direct sources natively, and auto-syncs results directly to your pipeline Kanban.

✨ Example Output Preview

Here is what the autonomous agent synthesizes for a candidate after analyzing their profile:

📁 Extracted Profile SummaryParsed GitHub + LinkedIn

Candidate exhibits **4+ years of software experience** focusing on full-stack generative AI deployments. Strong portfolio evidence of fine-tuning open-source models, vector database configurations, and semantic retrieval systems.

🛠️ Python🛠️ PyTorch🛠️ LangChain🛠️ RAG Systems
94% Match
Anthropic

Senior AI Software Engineer (Model Serving)

📍 San Francisco, CA (Hybrid) • 💼 Full-time
AI RATIONALE EXPLANATION:

"Candidate's GitHub repository showcases direct production implementation of asynchronous worker systems and streaming LLM tokens. This directly maps to Anthropic's pipeline requirements."

✅ EVIDENCE MATCHES:
  • Matches your GenAI repository code.
  • Demonstrates Python & PyTorch experience.
  • Seniority is compatible with project complexity.
⚠️ RISKS & GAPS:
  • Kubernetes preferred but missing from profile.
  • Requires 5+ years of production ML.