Automation Engineer

We build systems that run themselves — and we need an Automation Engineer who can design them. This role is about connecting APIs, databases, and LLMs into complex, multi-step workflows and AI agents that hold up in production, not demos that break the first time real data hits them. We're looking for someone with a genuine build history behind them, and we'll want to see it.

At the heart of the job is orchestration. You'll design and build multi-step workflows in n8n, Make, or similar, wiring together APIs, webhooks, and databases into reliable end-to-end systems. A growing part of that is AI: building agent workflows that pair LLMs like OpenAI and Anthropic with tools, data sources, and real decision logic — not just firing off a single prompt. You'll move structured data cleanly between steps, transform and parse it as needed, and make sure the right information lands in the right place.

What separates a working automation from a fragile one is everything around the happy path, and that's where we expect real care. You'll build in error handling, retries, logging, and monitoring so nothing fails silently, test thoroughly across edge cases, and troubleshoot broken workflows and integration issues when they come up. Every system you build should be documented clearly enough that someone else can maintain it, and tuned for reliability, speed, and cost over time.

On the experience side, we need proof you've built complex automations in n8n, Make, or Zapier, and that you've built LLM-powered agent workflows rather than just simple linear zaps. You should have a strong command of APIs, webhooks, authentication (OAuth, API keys), and JSON, plus hands-on experience integrating and querying databases like Airtable, Supabase, or PostgreSQL. Comfort with LLM APIs and structured outputs is essential, as is enough scripting in JavaScript or Python to handle custom logic when the no-code path runs out. Just as important: the ability to read unfamiliar documentation and integrate a new tool on your own, clear documentation habits, and strong written English. You'll need reliable internet and overlap with US business hours.

Strong bonuses include experience with vector databases and RAG, familiarity with agent frameworks and tool-calling patterns, prompt engineering for consistent output, and a track record of deploying and maintaining automations inside a real business.

To apply, show us what you've built. Walk us through 2–3 automations or AI agent workflows you personally created — the problem you were solving, the tools and APIs involved, how you handled data and errors, and how it turned out. Diagrams, screenshots, or a short walkthrough go a long way (blur anything confidential), and list the automation platforms, databases, and LLM tools you work with.