The Role
Mining operators don’t use Jupyter notebooks. They rely on dashboards, interfaces, and tools that run on tablets underground, on laptops at surface, and in control rooms operating under extreme conditions. You will build those systems.
As a Full-Stack Product Engineer, you will take the output from AI and ML teams and turn it into usable, high-impact applications for real users in the field. This includes operator-facing applications, data-intensive dashboards, and internal tools that support operations.
This is not a typical startup “full-stack” role. You will be building complex, domain-specific software for expert users who expect high performance and excellent UX.

What You’ll Own
Development of client-facing applications across multiple engagements
Platform interfaces and operational dashboards
Data visualization components (drill data, sensor streams, simulation outputs)
Integration between AI/ML backends and frontend applications
Demo environments and technical artifacts for business development
Internal tooling (automation, knowledge systems, workflow tools)




Performance and reliability in production environments

Who You Are

Experience
5+ years of full-stack engineering experience, with strong frontend expertise
Experience building internal tools or operator-facing applications (non-consumer)
Background working with data-intensive interfaces (dashboards, data grids, visualization-heavy UIs)
Experience in small teams with end-to-end ownership of features

Technical Skills
Frontend: React + TypeScript (advanced level), writing clean and maintainable component-based code
Backend: Python (FastAPI or similar) or Node.js
Data Visualization: Experience with D3.js, Vega-Lite, Recharts, or similar (building custom visualizations, not just using libraries)
Databases: PostgreSQL and/or time-series databases (InfluxDB, TimescaleDB), or vector databases
Deployment: Docker, cloud environments, CI/CD pipelines
Nice to have: WebGL or Three.js for 3D visualizations

📌 Fullstack Product Engineer (Argentina)
🏢 Squad
📍 Argentina