AI for Makers
We're Makers. In 2025, we set out to build something most teams only talk about. We embedded AI so deeply into our development workflows that we were over 10x more productive. Being on the bleeding edge isn't a strategy here. We hack on AI tools because we can't help it. It's how we're wired.

We don't talk about the future of engineering. We're living it. 

Logistics
This is a fully remote based role, however candidates must be located in Argentina or Brazil. Note: this is a long-term Independent Contractor position.

Please submit your resume in English.

Our tools & stack
- Python, MySQL, AWS
- Claude, Codex, Cursor, Copilot, LangChain, LangGraph, LangFuse, OpenRouter, FastMCP

What you'll do
- Push production AI agents into the platform's most complex flows. Build the MCP servers that orchestrate them: tool layer, context handling, model routing through OpenRouter
- Build the integration layer that powers the platform and the AI agents on top of it: identity, e-signature, real time data services. Every call has a user or an agent on the other end
- Build the rules engines, configuration runtime, and AI Copilots that turn the platform into a product factory. Customers ship entirely new products without us touching the code
- Bring whole companies onto the platform: importer pipelines, schema mapping, hard go-live dates. Every customer's data shape is different. Every cutover has a deadline that doesn't move
- Engineer the multi-tenant infrastructure companies run on. Async workers, document pipelines, scheduled jobs touching every site. The AI agent fleet is joining them tenant by tenant
- Design the public APIs the entire customer ecosystem runs on, with AI agents as first-class consumers and the contracts that let new endpoints ship at speed

What you'll bring
- Bachelor’s Degree or higher in Computer Science or a related field
- 5+ years of experience in Python web development
- 3+ years with SQL databases (e.g., MySQL, PostgreSQL)
- 3+ years of SaaS product development, including cloud based solutions
- 3+ years of hands on experience with Django or another Python framework
- 2+ years of proven experience building and consuming APIs
- Daily, deliberate use of agentic AI coding tools such as: Claude, Cursor, Codex
- Proven ability to direct AI agents on multi file, long horizon tasks
- Hands on experience with frontend frameworks like Vue.js or React
- Professional experience working with Docker for containerization and AWS
- Excellent verbal and written communication skills

Bonus points
- 2+ years of experience working at a scaling startup
- Experience with spec driven development: using AI to generate tests, scaffolding or architecture from requirements
- Hands on experience building production AI agents or multi-step LLM pipelines using LangChain, LangGraph, or equivalent orchestration frameworks
- Proven use of Agent Teams in Claude Code, multi agent orchestration via Codex, or similar parallel agentic workflows

We used tokens
This isn’t your typical AI generated job description

What did we do different?
Other companies: Basic AI
Us: Claude Cowork (Opus 4.7)

Why?
The same reason you’re still reading the job description

Here was our first prompt
I need to use Cowork to update a job description for a Senior Python Backend Engineer role. The current job description is in a folder on my desktop called "Job Description"

I want Cowork to pull from three Slack channels: #eng-general-int, #product-general-int and #ai-for-makers - plus any design docs from the last three months, to understand what we've actually been shipping. Then update the job description based on what it learns

Final output should be a Google Doc. Help me write the Cowork prompt

[Our recruiter wrote this prompt, not an engineer]