I am looking for an experienced n8n developer to build a flexible automated trading bot capable of executing any type of trading recommendations, for both Spot and Futures markets, without requiring a fixed signal format.
The bot should be able to receive, parse, and execute trading recommendations dynamically, regardless of how they are structured.
If you need, I am available here:
Here is my portfolio:
I’m also a full-stack developer with the right Gen AI experience, which makes me a solid plus for your team[but right now only vibecoding]
Check my recent gen ai projects… I built a native Android automation agent too. It’s worth a look:
I can build complex AI automations directly in code, not just inside n8n
I recently started posting my n8n work on YouTube with explanations:
https://youtube.com/@blankarray
Fun fact… I even made an n8n workflow to find a few n8n project leads for myself so I truly believe in what I do…
Here is my linktree: iamvaar | Linktree
Apart from this I am capable of creating custom n8n nodes too:
And I also built low latency voice appointment scheduler with live ai avatar:
I built AI search visibility tracker:
Hi Jack, I can build this bot for you. But needs to know what type of markets yoy’re trading? Crypto or FX? If crypto, are you trading on CEX or DEX. The environments are pretty different, and the requirements vary a lot. If you can provide more information, then I can help build this out for you. Please send me an email: [email protected].
Or book a call here to explain the requirements > 30 min meeting | Ola | Cal.com
You can also send me a DM on telegram if you’d prefer texting > Telegram: Contact @whiskey345
Happy to help!
Subject: Expert n8n Developer | Dynamic AI-Powered Trading Automation
Hi there,
I saw your requirement for a flexible n8n-based trading bot, and this is exactly within my wheelhouse as an AI Automation Engineer.
I specialize in building “Agentic” workflows that don’t rely on rigid formats. To solve your “fixed signal” problem, I implement a dynamic parsing layer using LLMs within n8n to interpret unstructured recommendations (from Telegram, Discord, or Email) and convert them into structured JSON for Spot or Futures execution.
Why I’m a fit for this:
Dynamic Parsing: Experience building n8n workflows that handle non-standardized data inputs.
Multi-Market Execution: Proficient in integrating exchange APIs (Binance, Bybit, etc.) for both Spot and Futures.
Error Handling: I build robust logic for slippage, leverage management, and real-time alerts.
You can view my portfolio and previous automation projects here: https://docs.google.com/document/d/1FG8Dm8UtDLnSJi3Zyw3Uwg0BasIIiVXmm78eIRPwcrA/edit?usp=sharing
I’d love to discuss how I can build this flexible architecture for you. Are you available for a quick chat?
AI Automation Engineer
Best regards,
Naresh Nayak
I can help you build a flexible automated trading bot using n8n. The bot will be designed to receive, parse, and execute trading recommendations for both Spot and Futures markets, adapting dynamically to various input formats. Let’s discuss the project further to ensure it meets your specific needs.
Book a quick call:Calendly - Automaxion
Hi! @Jack11
The safe way is to turn “any format” recommendations into one internal schema, then only execute when validation passes.
In n8n, add a “Parse” step (rules + optional LLM) that normalizes everything into {exchange, spot/futures, symbol, side, entry, size, leverage, SL, TP[], time-in-force}
Add a strict “Validator + Risk Gate” (required fields, price sanity checks, leverage caps, max risk/day, idempotency so you don’t double-fire)
Only then route to the exchange executor nodes, with dry-run mode, full logging, and a dead-letter queue for ambiguous/failed messages
That gives you flexibility without placing trades off unclear text and protects against duplicates/overwrites.
I’ve built similar “free-form input → structured action” agent workflows in production, where the model extracts fields but deterministic gates control execution. Happy to share sample schemas, parsing prompts, and retry/idempotency patterns if helpful.
Portfolio: Case Study
Reviews: Clutch
Book a call: Calendly
Yes I’ve actually built something very similar before.
I built an n8n-based trading automation that:
• Pulled live market data using exchange/market APIs
• Dynamically identified tickers
• Ran technical analysis (RSI, MACD) to detect momentum and trend shifts
• Generated structured trade-style recommendations
• Delivered the output as a clean, readable email alert
Example output looked like:
Stock Alert: APLM
APLM surged 47.78% before trading was halted by Nasdaq
Price: $18.00
Volume: 682,277
Sentiment: Somewhat-Bullish
All of this was orchestrated in n8n with custom logic, validation, and error handling not a fixed signal format.
@Jack11 I’ve built production n8n systems that handle unstructured inputs → normalized execution logic, including dynamic parsing and API-based execution.
A flexible Spot & Futures trading bot is doable with the right signal-normalization and risk layer.
Happy to discuss details.
Email: [email protected]
Portfolio: https://www.muhammadz.fun/
Projects: https://muhammad-ai-automations.notion.site/Muhammad-Bin-Zohaib-AI-Automation-Projects-29da292a241380f889c2e337a134c010
Hi 
This sounds like an interesting project.
I’m an automation developer with hands-on experience using n8n to build flexible, logic-driven workflows. I’ve worked on systems that dynamically parse unstructured inputs, apply custom logic, and execute actions based on variable conditions — which aligns well with your requirement of handling non-fixed trading signal formats.
My approach would be:
• Normalize incoming signals (from any source/format)
• Use dynamic parsing and validation logic
• Support both Spot & Futures execution
• Implement risk controls, error handling, and logging
• Keep the system modular so strategies can evolve over time
If you can share:
• Signal sources (Telegram, webhook, API, etc.)
• Target exchanges
• Execution rules / risk preferences
I’d be happy to discuss the architecture and next steps.
Feel free to DM me here and we can take it forward.
Thanks!
Subject: Proposal: Automated Trading Signal Infrastructure (n8n/Python)
Hi,
I came across your project regarding dynamic trading signal automation, and it aligns perfectly with the work we do at Piorate Ventures.
I specialize in building self-healing, logic-driven workflows using n8n and Python. My focus is on systems that can ingest messy, unstructured data (like varied Telegram signals), normalize it into a standard JSON format, and execute trades with strict risk management.
My Proposed Architecture:
Normalization Layer: A parsing engine that standardizes signals from any source (Telegram, Discord, Webhook).
Logic Core: Dynamic validation rules to filter “bad” signals before they hit the exchange.
Execution: Support for both Spot & Futures with customizable leverage/TP/SL settings.
Safety: Automated error logging and “Kill Switch” protocols to protect capital.
To give you an accurate roadmap, could you share:
Sources: Are we listening to Telegram channels, Discord, or direct Webhooks?
Exchanges: Is this for Binance, Bybit, or another specific exchange?
Risk Logic: Do you need fixed position sizing or dynamic calculation based on account balance?
I’d be happy to walk you through a similar “Signal-to-Execution” workflow I’ve built.
Portfolio: https://docs.google.com/document/d/1FG8Dm8UtDLnSJi3Zyw3Uwg0BasIIiVXmm78eIRPwcrA/edit?usp=sharing
Best regards,
Naresh Nayak
Hi there! Feel free to check out our profile – if it seems like a good fit, we’d be more that happy to connect and discuss how we can support your project. Contacts
Hey man, I’m actually a day trader and an n8n developer. I have just been going over a plan to create an auto trading Futures bot, Utilizing n8n, AI, and some general base logic. Ideally passing to mt5 for execution. Let me know if you want me to look over your project, and see if its a good fit.
