Imagen institucional
Imagen institucional

Ssr. AI Engineer

Buenos Aires, Buenos Aires, Argentina

Tecnología, Sistemas y Telecomunicaciones/Tecnologia / Sistemas

Full-time
Remoto

Hace 22 días

Postularse

Hace 22 días

Buenos Aires, Buenos Aires, Argentina

Tecnología, Sistemas y Telecomunicaciones/Tecnologia / Sistemas

Full-time
Remoto

Hace 22 días

Postularse
Descripción del puesto

🔍 We are looking for an AI Engineer to join a Continuous Integration team. This role will be key in designing, developing, and deploying AI microservices, working with cutting-edge frameworks like Langchain and LangGraph within a scalable cloud-native architecture.

💡 Main responsibilities:

  • Build and deploy AI microservices in Python.

  • Design scalable multi-agent systems.

  • Use Docker and Kubernetes for containerization and orchestration.

  • Integrate AI services into CI/CD pipelines.

  • Collaborate with data science, DevOps, and product teams to bring AI from research into production.

🌐 What the company offer: the opportunity to work at the intersection of AI innovation and cloud-native technologies, contributing to the development of our next-generation enterprise platform.

Requisitos

Requirements

  • Python: Proficient in Python programming, with experience in developing AI applications and microservices.
  • Langchain: Expertise in Langchain framework for building AI applications that integrate language models with external data and tools
  • LangGraph: Experience with LangGraph for constructing and managing graph-based AI workflows and decision-making processes
  • Microservice Architecture: Strong understanding of microservice design principles, including service decomposition, API design, and inter-service communication
  • Multi-agent Systems: Proven experience in designing and deploying multi-agent AI systems that enable autonomous, collaborative, or competitive agent behaviors
  • MCP Reverse Proxy: Knowledge of MCP Reverse Proxy configurations and management to facilitate secure and efficient routing of AI microservices
  • Enterprise Platform Deployment: Familiarity with deploying AI solutions within enterprise-grade platforms, ensuring scalability, security, and compliance
  • Docker and Kubernetes (K8s) Experience: Hands-on experience with containerization using Docker and orchestration with Kubernetes, including deployment, scaling, and management of containerized AI services

Beneficios

💵 Contractor

🌍 100% remote

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