Engineering
Automation Engineer
You connect agents to the systems where the client actually works, and leave those flows observable and failure-proof.
RemoteObjective-basedNo minimum years · evidence required
Apply for this role About Hopper Labs
We are a Chilean AI consultancy. We design, build, and maintain bespoke operational agents for mid-market and enterprise companies. We work as an end-to-end operating partner: scoping, build, integration, and support, with no dev team required on the client side. The commitment is measurable ROI in under 90 days.
About the role
Agents are useless if they do not touch the systems where the client actually works. You build and maintain those integrations and automations, and leave them running without anyone having to watch them every day.
Applies to every role
- 100% remote. Where you are does not matter.
- We work against objectives, not hours. You decide when you work.
- We hire builders: autonomous people with taste, focused on quality and on adding real value.
- Real autonomy: you get a business problem, not a ticket with the solution already written.
- Technology and AI genuinely move you: you try the newest thing as it lands, you follow how the market is adapting to these tools, and you want to work out how to put them to use. We look for curious people who are deep in the industry.
What this role works with
n8nGoogle CloudWhatsApp BusinessSupabaseApolloInstantlyVapiMercadoPagoJavaScript / TypeScriptVercel
Responsibilities
- Build automations and workflows: webhooks, queues, retries, error handling, and alerting.
- Integrate third-party APIs: WhatsApp Business, Google Workspace, CRMs, ERPs, accounting systems, e-commerce platforms.
- Document every automation so someone else can operate it without you.
- Monitor executions and reduce manual intervention month over month.
Requirements
- We do not ask for years or a degree: we ask for evidence. You must be able to show automations of yours, in use, that saved someone money or time.
- Real command of n8n, Make, or equivalents at scale, not demos, things running in production.
- JavaScript for code nodes and for the glue the tool does not cover.
- REST, webhooks, OAuth2, and payload debugging without losing your mind.
- Understanding of where an LLM belongs in an automated flow and, above all, where it does not.
What we look for
- An autonomous builder: hand you a manual process and you come back with it automated.
- Obsession with robustness: every flow has to survive the day the API on the other end goes down.
- Taste and a focus on quality: you prefer a simple flow anyone can read over a clever one nobody can touch.
- The ability to talk to a client and turn 'I need this to happen by itself' into something concrete.
How the process works
1
Apply
CV and links
2
Call
30 minutes
3
Challenge
Short and paid
4
Offer
Final conversation
Two weeks end to end, at most.
Engineering & client
AI Solutions Consultant