Compensation:
• $1,500 USD per month
• Payments are made exclusively via Wise
We are looking for an experienced n8n developer to build and maintain AI-powered automation workflows.
Requirements:
• Strong experience with n8n
• Experience building AI automation systems and workflows
• Knowledge of LLMs such as ChatGPT, Claude, Gemini, etc.
• Strong prompt engineering skills
• Experience creating automations for tasks such as script generation, content creation, research, and AI-assisted workflows
• Ability to integrate APIs and third-party tools
• Strong problem-solving skills and attention to detail
• Good written and spoken English
Nice to Have:
• Experience with Python or JavaScript
• Experience with vector databases, RAG systems, or AI agents
• Familiarity with video, content, or social media automation workflows
Responsibilities:
• Design and build AI-powered workflows in n8n
• Create and optimize prompts for reliable AI outputs
• Integrate AI models and external services
• Improve workflow performance, scalability, and reliability
• Troubleshoot and maintain existing automations
To Apply:
Please send:
• A 5–7 minute Loom video covering:
1–3 relevant projects you have built
The most complex system or automation you have ever developed
Why you believe you are the right fit for this role
• Your portfolio
• Your contact information
• Examples of AI automation workflows you have built
Interested candidates should contact me on Discord: ymagic.hiring
At Blukaze Automation, we build production-ready n8n workflows, RAG systems, and custom AI agent integrations designed for reliability, scalability, and seamless integration with your existing stack.
This is a strong fit for me — n8n + LLM (Claude/GPT/Gemini), prompt engineering for reliable outputs, API integrations, and keeping workflows running so they don’t silently break.
Quick proof of how I work: I actually found this job through my own system. I don’t sit on job boards all day — I built a small pipeline that monitors automation job sources, scores each post with an LLM for relevance, filters out noise, and delivers only the real matches to me. So the way this posting reached me is itself a working example of what you’re hiring for: scraping → LLM scoring → filtering → delivery, running unattended in the background.
The architecture behind it is exactly the kind of thing your role needs: a collector and a scorer decoupled through a database queue, LLM-based classification, retry logic, process isolation (a failure in one part doesn’t break the rest), and a human-in-the-loop step — nothing auto-sends, I review before acting.
I also run LingoVox (lingovox.online, @lingovoxbot on Telegram) — a voice translation bot live in production with paying users. Python + Postgres + OpenAI API, deployed with auto-restart, handling real payments and daily usage. So I have a touchable product, not just demos.
A couple of questions to see if we fit:
What’s the expected monthly workload — is the $1,500 for full-time hours, or part-time / per-task?
Roughly what kinds of workflows are first in the pipeline?
Interested in this role — I’ve built multiple AI automation systems using n8n with LLM integrations (ChatGPT, Claude, etc.), API workflows, and scalable agent-based automations.
I can design, optimize, and maintain reliable workflows for content generation, research automation, and AI-assisted business processes.
This fits the kind of work I can take on: n8n-style AI workflows, LLM prompts that return reliable JSON, API/webhook integrations, and Python/JS helpers when a visual node is not enough.
Instead of a long hiring loop, I would be happy to start with a paid USD 500 test workflow so you can evaluate delivery before the monthly Wise arrangement.
Relevant proof I can share as a packet:
Lead automation: intake/scrape → AI qualification → dedupe → outreach draft → run log and follow-up queue.
RAG/support demo: document Q&A with retrieval, clear citations, and fallback behavior.
Most complex build pattern: an agent-style pipeline that separates collection, scoring, approval, sending, and bounce/reply monitoring so no workflow marks work done without verified data.
I can send the portfolio packet / importable workflow examples by email, and record the 5-7 min Loom if the official process requires it. Contact: ysru150623@gmail.com
Happy to do one scoped test: choose a content/research workflow, I map inputs/outputs, build the n8n flow plus JS/Python helpers, add retries/logging, and hand over notes.
Magic1, I’m Misha, an n8n and AI automation developer. I’d build and maintain your AI workflows by designing modular nodes that handle script generation, content creation, and research reliably, with retry logic and logging to keep them running. I’m strong on prompt engineering for LLMs like ChatGPT and Claude, and I’d wire up APIs for third-party tools like video or social media platforms directly in n8n. For complexity, I’ve built systems that combine vector databases and RAG to make AI outputs more accurate, and I can add Python steps where n8n alone needs extra flexibility. You’ll get stable automations that don’t need constant babysitting. I’m ready to send a Loom video covering my top three relevant builds right away. Portfolio: https://mikedevai.netlify.app/ | Telegram: Telegram: Contact @hely_chatbots | WhatsApp: +375293761570
I saw your post on the n8n community forum regarding the AI Automation Developer role. I am Swapnil, an AI Automation Engineer and founder of Swapnil AI Labs.
I have extensive experience building and maintaining production-grade AI automation systems in n8n, ranging from agentic workflows to complex RAG pipelines. I’ve spent the last several months scaling business operations through intelligent automation, and I am confident I can handle the reliability, prompt optimization, and performance requirements you’ve outlined.
My Approach & Portfolio:
Technical Focus: I specialize in high-reliability workflows, incorporating error handling, state management, and robust LLM integration (Claude, GPT, etc.).
Complex Systems: I have experience architecting systems for research, content creation, and automated data processing, which aligns directly with the tasks you mentioned.
Next Steps: I am currently preparing the 5-7 minute video covering my project architecture, the most complex automation I’ve built to date, and my integration methodology.
Are there any specific “problem areas” in your current workflow you are looking to prioritize first? I would love to frame my video case study around those challenges to show exactly how I would solve them.
Hi @Magic1, this looks like a strong fit: n8n + LLM workflows, API/webhook integrations, prompt reliability, and small Python/Node helpers when a workflow needs custom logic.
I can help with content/research automation, script-generation pipelines, approval gates, retries/logging, and clean workflow handoff notes. I am available for a paid scoped test first if you want to validate delivery before a monthly Wise arrangement.