I'm looking to work with a growth-focused agency that needs a dedicated automation engineer who can handle the technical infrastructure that powers client delivery. --What I Bring 2+ years building production-grade automation systems across: n8n workflows – complex multi-step automations with error handling and monitoring API integrations – connecting platforms that weren't meant to talk to each other CRM automation – lead routing, data enrichment, pipeline management Operations automation – reducing manual work across sales, support, and delivery Backend systems – building the infrastructure that keeps things running reliably I own projects end-to-end: design the architecture, build it, test thoroughly, set up monitoring, and document everything so it doesn't break at 2 AM. My approach: Build things that work long-term, not quick fixes that need constant maintenance. -- What I'm Looking For I want to work with an agency that has: ✅ Consistent workload – 20–24+ hours per week ✅ Long-term vision – building a relationship, not one-off projects ✅ Clear expectations – I know what needs to be done, you know what you're getting I'm not looking for: Revenue-share or commission-only arrangements Inconsistent "we'll reach out when we need you" work Projects that disappear for weeks between tasks -- What I Can Own Once we're working together, I can take full responsibility for: Building new automation systems from scratch Maintaining and improving existing workflows Integrating new tools into your tech stack Setting up AI-powered workflows that actually deliver value Troubleshooting issues before clients notice them Creating documentation so your team understands how everything works -- Let's Talk If your agency has steady automation work and you're looking for someone who can become a reliable part of your operations team, I'd like to connect. On pricing: I prefer discussing pricing privately, but I’m flexible and open to working at a lower hourly rate as long as the work is consistent..

I’m exploring advanced agent-based architectures in n8n where a primary AI agent can design, configure, and deploy secondary agents autonomously based on task requirements. Specifically, I’m trying to understand: - How to architect an agent supervisor / orchestrator pattern in n8n - Whether people are using meta-agents that generate: - Best practices for doing this with: - Guardrails for: I’m not looking for “auto-GPT style demos,” but production-grade patterns that work reliably inside n8n. If anyone has: - architecture diagrams - workflow patterns - real-world examples - or lessons learned from failed attempts I’d really appreciate insights.