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Build Agentic LinkedIn Engagement System – LLM + Automation + Human-in-the-Loop

Search - AI Chatbot · ai_analyzed · UID ~022083220813805793914

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Job Details

Budget Unknown
ExperienceExpert
DurationUnknown
Weekly hoursUnknown
Client countryAbout the client
Proposals5 to 10
Interviewing2
Invites sent26
First seenFri, Jul 31, 2026 7:12 PM
Last seenSat, Aug 1, 2026 12:49 AM

Description

Summary We are looking for an experienced engineer/automation specialist to build an agentic workflow that drives brand awareness in our ecosystem via intelligent LinkedIn engagement. Objective: Identify high-signal conversations, generate thoughtful responses using LLMs, and automate posting—with human approval in the loop. Scope of Work: 1) Data Sourcing - Identify and extract the latest ~5,000 posts in our ecosystem (LinkedIn or relevant sources) - From that dataset, isolate unique authors and select one high-quality post per author 2) LLM-Based Content Generation - For each selected post: - Generate 3 alternative responses - Each response must be 2–3 lines maximum - Responses must be context-aware, insightful, and aligned with the original post (not generic comments) 3) Human-in-the-Loop Review - Build a lightweight interface or workflow (could be Notion, Airtable, or custom UI) where: - A reviewer selects the best of the 3 generated responses - Option to edit before approval 4) Automated Posting - Once approved: - Automatically post the selected response via LinkedIn (using Sales Navigator account) - Ensure compliance with LinkedIn limits and best practices 5) Agentic Workflow Design - The system should: - Run continuously or on schedule - Improve over time (prompt tuning, feedback loops) - Be modular and scalable Tech Expectations: - Strong experience with APIs, scraping, or data sourcing (LinkedIn-safe approaches preferred) - Experience with LLMs (OpenAI, Claude, etc.) and prompt engineering - Workflow automation (Zapier, Make, n8n, or custom Node.js/Python) - Experience building human-in-the-loop systems - Understanding of LinkedIn automation constraints and best practices Success Criteria: - High-quality, relevant comments (not spammy) - Consistent daily output - Increased engagement and brand visibility over time Speed is critical. We are looking to move fast and iterate quickly.

Skills

Python API LinkedIn Recruiting Automation Data Scraping

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