LinkedIn Content publisher RAG Model

Title: Build Automated RAG System for Daily LinkedIn Carousel Posting

Description:

I am looking for an experienced AI Automation / RAG Developer to build an end-to-end system that automatically generates and publishes LinkedIn carousel content every day at 6:00 AM.

Project Requirements:

• Build a Retrieval-Augmented Generation (RAG) system using a knowledge base consisting of PDFs, documents, articles, notes, or other content sources.
• The system should retrieve relevant information from the knowledge base and generate unique, high-quality LinkedIn carousel content daily.
• Create carousel content in a Canva-style format (8–10 slides preferred), including:

* Hook slide
* Educational/value-driven content slides
* Summary or CTA slide
• Schedule the workflow to run automatically every day at 6:00 AM.
• Automatically export the carousel in a LinkedIn-ready format (PDF or images).
• Publish the generated carousel directly to my LinkedIn account via API/integration.
• Maintain a log of generated topics to avoid duplicate content.
• Provide a simple dashboard or management interface to upload new documents and manage the knowledge base.

Preferred Skills:

• RAG systems (LangChain, LlamaIndex, Haystack, etc.)
• Vector databases (Pinecone, Qdrant, Weaviate, ChromaDB)
• OpenAI, Claude, or Gemini APIs
• LinkedIn API integration
• Canva API or automated carousel generation
• Workflow automation (n8n, Make, Zapier, Airflow, Python)
• Cloud deployment and scheduling

Nice to Have:

• Experience building AI content automation systems
• Experience with LinkedIn growth/content workflows
• Ability to suggest improvements for content quality and engagement

Deliverables:

✔ Fully functional automated RAG pipeline
✔ Daily scheduled execution at 6:00 AM
✔ Automated LinkedIn carousel generation
✔ Automatic LinkedIn publishing
✔ Documentation and deployment instructions
✔ Source code and ownership transfer

When applying, please share:
• Similar AI automation or RAG projects you have built
• Technology stack you recommend
• Estimated timeline and cost
• Any suggestions for improving the workflow

I am looking for a reliable developer who can build a scalable solution that requires minimal manual intervention once deployed.