AI Automation Engineer — Agents, MCP, Voice AI, n8n & Power BI

We’re looking for an AI Automation Engineer who enjoys taking a messy business process and turning it into something that simply works. Here’s the kind of problem we’re trying to solve: A customer calls a business. An AI voice agent answers, understands what they need, checks the right information, qualifies the opportunity, books an appointment, updates the CRM, and triggers the follow-up workflow. The business owner can then see the results through a Power BI dashboard. The AI shouldn’t just have a conversation. It should be able to get things done. That’s where we need your help. What you’ll be building AI agents that can reason, use tools, and complete business tasks MCP servers and tools to connect agents with external systems AI voice agents for inbound and outbound calls n8n workflows connecting CRMs, APIs, databases, WhatsApp, email, calendars, etc. LLM integrations with OpenAI, Claude, Gemini, or the right model for the job RAG and knowledge bases where agents need access to company information Automated data pipelines and Power BI dashboards/reporting Reliable error handling, logging, retries, and human handoffs What we’re looking for You don’t need to know every tool listed above. We care more about real experience and good engineering judgment. You should be comfortable with: Python or Node.js/TypeScript REST APIs, webhooks, OAuth, and databases AI/LLM APIs and agent workflows n8n or similar automation platforms MCP and tool-based AI integrations Voice AI and telephony integrations Power BI and business reporting Deploying and maintaining production systems Most importantly, you’ve actually built things. You know that getting an AI demo to work once is easy; making it reliable when real customers, APIs, failures, and edge cases are involved is the real job. When you apply Please don’t send us a generic AI developer proposal. Show us 2–3 relevant projects you’ve personally built and briefly explain what the system did, what you were responsible for, and which technologies you used. Loom demos, live products, or GitHub repositories are highly appreciated.