Customer-Facing AI Deployment Engineer

Enlighten AI Labs

Ciudad de México

Presencial

MXN 700.000 - 1.100.000

Jornada completa

Hace 4 días
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Descripción de la vacante

Enlighten AI Labs is seeking a software engineer to build and deploy applications in collaboration with customers. You will own a deployment component from investigation through handoff, working with senior engineers on decisions affecting the system.

You will run AI agents in parallel, develop features, and ensure integration quality while maintaining clear communication with customers and team members.

Formación

  • Shipping working software with demonstrated investigations and delivery.
  • Proficient in Python or TypeScript, SQL, APIs, and modern practices.
  • Comfort learning unfamiliar data platforms, applications, and customer workflows.
  • Experience with cloud platforms, data warehouses, or customer-facing technical delivery.
  • Experience with React, FastAPI, automated testing, or AI workflow orchestration.
  • A small app, automation, or open-source contribution you can explain.

Responsabilidades

  • Understand user needs with customers and delivery leads.
  • Build and test application features, integrations, and data transformations.
  • Run multiple AI agents in parallel to map systems and prototype fixes.
  • Reproduce and diagnose issues across APIs, datasets, and applications.
  • Write tests and handoff notes; flag scope changes and production risks.
  • Own the result and verify facts before decisions or releases.
  • Collaborate with teammates and customers.

Conocimientos

Python
TypeScript
SQL
APIs
Cloud platforms
Data warehousing
React
FastAPI
Automated testing
AI orchestration
Software development

Herramientas

Open-source projects

Descripción del empleo

Enlighten AI Labs is seeking a software engineer to build and deploy applications in collaboration with customers. You will own a deployment component from investigation through handoff, working with senior engineers on decisions affecting the system.

You will run AI agents in parallel, develop features, and ensure integration quality while maintaining clear communication with customers and team members.

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