2 publicaciones de empleo destacadas en senior data engineer ai integrations, mcp & (¡Están contratando!)

Senior Full Stack AI Engineer Azure AI Foundry
Publicis Groupe Holdings B.V —Cuauhtémoc, CDMX
- Azure
- JavaScript
- Python
Postulación rápida
5h
Backend Developer - LATAM
OrderMesh —México
- Home Office (Desde casa)
- DevOps
- Mejora continua
- Experiencia en manufactura
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Senior Full Stack AI Engineer Azure AI Foundry
Publicis Groupe Holdings B.V —Cuauhtémoc, CDMX
Strong backend engineering and API development experience (Node.js preferred or Python). Contributions to developer productivity, internal platforms, or…
Postulación rápida
5h
Backend Developer - LATAM
OrderMesh —México
Experience in ecommerce or supply chain domains. Build and optimize data layers using MongoDB and Redis. Experience using AI coding tools such as Claude Code or…
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Senior Full Stack AI Engineer Azure AI Foundry

Publicis Groupe Holdings B.V -
Cuauhtémoc, CDMX

Postulación rápida

Información del empleo

Hace 5 horas

Cualificaciones

Azure
Node.js
Ingeniería de software
React
JavaScript
Seguridad
Requisitos comerciales
TypeScript
Python

Descripción completa del empleo

We are seeking a Senior Full-Stack AI Engineer to build and scale enterprise-grade AI applications, agents, copilots, and workflow automation solutions. This role is focused on building and scaling enterprise AI solutions on Azure, with a strong emphasis on Azure AI Foundry.

The engineer will design, implement, and operate AI-powered applications such as agents, copilots, and workflow automation, integrating them into existing enterprise systems through robust APIs. Front-end capabilities are important to enable usable AI experiences, with React considered highly desirable, but deep Azure AI engineering expertise is the primary driver of success in this role.

Your Impact

Design and deliver production-grade AI applications (agents, copilots, automation workflows) with a strong focus on Azure AI Foundry and Azure-based AI services.
Build and maintain backend services and APIs (e.g., Node.js or Python) that integrate AI capabilities into enterprise systems.
Integrate internal and external systems via secure APIs and MCP-style integration patterns, enabling extensibility and orchestration.
Implement robust engineering practices to ensure quality, security, and maintainability in AI-enabled systems (testing, monitoring, CI/CD).
Partner with cross-functional teams to translate business requirements into reliable AI-powered features and workflows.
Review and validate AI-generated outputs and code, applying strong engineering judgment to avoid low-quality or insecure implementations.
Contribute to front-end experiences for AI products; React/TypeScript is preferred, but equivalent modern web UI experience is acceptable.

Skills & Experience

8+ years of professional software engineering experience delivering production systems.
Mandatory: Hands-on experience building AI solutions on Azure, with direct experience using Azure AI Foundry.
Experience building enterprise AI applications such as agents, copilots, workflow automation, or AI-enabled product features.
Strong backend engineering and API development experience (Node.js preferred or Python)
Experience integrating systems through APIs; familiarity with orchestration/integration patterns (including MCP-style approaches).
Front-end development capability for modern web applications; React + TypeScript strongly preferred.
Experience with cloud engineering practices (CI/CD, observability, containerization) in production environments.
Strong engineering standards: code quality, testing discipline, security mindset, and performance/scalability awareness.

Set Yourself Apart With

Experience designing end-to-end AI workflows and agent architectures deployed in production.
Strong experience operating within Azure environments (security, governance, monitoring, scalable deployments).
Experience with event-driven systems and asynchronous communication patterns.
Comfort reviewing AI-generated code and outputs with a pragmatic, risk-aware mindset.
Contributions to developer productivity, internal platforms, or reusable engineering frameworks.

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