We are seeking a seasoned n8n Cloud Automation Developer to architect and build a cutting-edge, multi-agent AI workflow. You will be responsible for designing an n8n flow in which:
AI Agent #1 ingests and analyzes multiple incoming documents.
Based on that analysis, Agent #1 dynamically generates a tailored prompt.
AI Agent #2 receives the Agent #1 prompt, executes further domain-specific logic, and issues instructions to downstream AI nodes.
Your work will turn these document reviews into fully automated, intelligent pipelines—streamlining our process and enabling rapid, reliable reports.
How to Apply
Please email your application to [email protected] with the subject line:
Application: n8n AI Agent Workflow Developer
Include the following in your message:
Required (please include):
A brief cover letter outlining your n8n and AI orchestration experience.
Your résumé/CV.
A short sample (2–3 paragraphs) describing a past n8n project where you chained multiple Function or Agent nodes.
Your availability and expected weekly hours.
Optional (will give your application a boost):
Links to any public n8n workflows or repositories you’ve created.
Testimonials or references from previous clients or colleagues.
A one-page architecture sketch of how you’d structure a multi-agent AI flow in n8n.
We review applications on a rolling basis and aim to schedule technical interviews within five business days. Thank you for considering this opportunity to help us blend time-honored precision with tomorrow’s AI-powered automation.
This is a well defined and exciting opportunity. I’m aligned with the technical vision, especially around orchestrating multi-agent AI flows using n8n.
Just wanted to let you know I’ll be sending over a detailed application shortly to the email provided. Looking forward to the chance to collaborate on this.
Thanks for sharing the opportunity — it aligns closely with the kind of AI-driven automation work our team excels at.
We’re a team of 10+ experienced automation developers, well-versed in designing complex, multi-agent workflows using tools like n8n, LangChain, and OpenAI. While I won’t claim we’ve built this exact flow before, we’re confident in our ability to understand your use case, break it down into scalable logic, and deliver a reliable, production-ready system.
If you’d like, I can share more about our past AI orchestration work, availability, and next steps. Let’s connect to explore how we can help bring your workflow to life.
I’m Moataz Towfik, an Integration & Automation Engineer with strong hands-on experience in n8n, along with tools like TIBCO, MuleSoft, Jenkins, and Docker.
I’ve used n8n extensively to build custom automations, API integrations, and workflow orchestration for real-world business needs—especially in my roles at Vodafone and AlexBank. From simple triggers to complex branching flows, I know how to make n8n work efficiently and reliably.
If you’re looking for a freelancer who can jump in and deliver fast, scalable results—I’m ready.
I got you, I have been building all forms of automations for the past 2 years and have built 100s of flows for my clients. Have worked with all sorts of companies and gotten them 10s of thousands in revenue or savings by strategic flows. When you decide to work with me, not only will I build this flow out, but also give you a free consultation like I have for all my clients that led to these revenue jumps.
I have built a similar workflow like this for one of my clients. I can not only share that but also how you can streamline processes in your company for faster operations. All this with no strings attached on our first call.
Here, have a look at my website and you can book a call with me there!
It sounds like you want to orchestrate multiple AI agents that turn document reviews into an automated pipeline. A structure that has worked for similar projects is:
Ingestion and normalisation: use the Read PDF or Read Binary File node to pull each document, convert it to JSON, and store it temporarily so later agents have consistent input.
Prompt builder: place Agent 1 logic inside a Function node that assembles a dynamic prompt based on the JSON. Add an IF node afterwards with continue-on-fail so the flow never stalls on an empty prompt.
Specialist processing: run Agent 2 in an OpenAI node. Control temperature and max-tokens with environment variables and enable Concurrency control to avoid rate limits if volume grows.
Practical tips:
Wrap each agent section in a Sub-workflow so you can unit-test them independently.
Turn on execution logging and keep at least 30 days of history; catching edge-case documents early saves a lot of time.
Add a Merge (Wait) node before any downstream writes so you are sure both agents have completed.
A few questions to help size the effort:
• Approximately how many documents per day do you expect?
• Do you have a preferred storage layer for intermediary outputs (database, object storage)?
• Is there a target processing time per document that the business requires?
This is general guidance based on my experience with similar projects.
Hi @Mohammed-GCS
I’m Yusuf Opeyemi, an experienced workflow automation expert and chatbot developer, specializing in n8n, the powerful open-source automation platform.
Over the past few years, I’ve helped startups, agencies, and small businesses save countless hours and increase productivity by building smart, scalable, and reliable automations. Whether you need to streamline your CRM, automate lead generation, integrate APIs, or build a custom chatbot I’ve got you covered!
What I Can Do for You:
Design and build robust n8n workflows for any business process.
Integrate your tools (like Slack, Airtable, Google Sheets, WhatsApp, Stripe, etc.) seamlessly.
Create API-based automations to connect custom apps and services.
Build and deploy chatbots for WhatsApp, Messenger, websites, or Telegram.
Debug and optimize your existing workflows to make them faster and more reliable.
Provide guidance and training so you can manage your automations confidently.
Let’s Connect!
If you’re ready to save time, cut costs, and focus on what matters while automation handles the rest
let’s chat!
Feel free to reach out and tell me about your project. I’ll be happy to help bring your automation ideas to life
Based on my experience with similar automations, it sounds like you’re aiming to turn a multi-document review process into a fully autonomous pipeline driven by collaborative AI agents.
I’ve built comparable n8n architectures where Agent-1 handles classification & prompt generation, handing structured context to downstream logic executed by Agent-2. Using n8n’s Execute Workflow webhook pattern together with OpenAI nodes, we reduced manual document analysis time from hours to minutes.
A practical rollout could look like this:
• Start with a minimal flow that ingests two sample document types, generates a prompt, and returns a draft summary.
• Iteratively expand Agent-2 logic by adding condition branches and external API calls once the core hand-off is stable.
• Containerize the flow so it can scale horizontally inside n8n Cloud or self-hosted Docker.
First action step to keep momentum: define the specific document formats and desired output schema so each agent can operate with clear contracts.
Strategic question: Beyond report generation, what other downstream decisions will these insights power (e.g., task creation, CRM updates, compliance checks)?
Happy to compare notes on best practices and pitfalls when connecting multiple AI nodes in production n8n environments.
