AI Systems Engineer: Multi-Agent & LLM Production

Globant; Nuevo León; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Globant is seeking an AI Engineer to design, build and deploy agentic AI systems for production. You will architect multi-agent workflows, integrate LLMs and external tools, and ensure reliable operation through prompt engineering and guardrails.

The role requires 5–10 years of software engineering experience, strong Git-based workflows, and hands-on cloud experience with AWS or Azure. You will own delivery timelines and contribute to scalable AI pipelines.

Formación

• Hands-on experience designing and deploying agentic AI systems.
• Experience with LLM tool calling and API integrations.
• Knowledge of prompt engineering, context management and failure modes.
• Ability to design architecture for model and agent pipelines, testing and observability.
• Experience with HITL workflows and sandbox isolation.

Responsabilidades

• Design and develop AI systems with multiple agents collaborating to complete complex workflows.
• Implement guardrails for safety, compliance, and performance monitoring.
• Ship production-ready AI solutions and iterate quickly based on model releases.
• Define and improve CI/CD pipelines and deployment strategies.

Conocimientos

Agentic experience

LLMs and multi-agent frameworks

Prompt engineering

Tool use and API integrations

CI/CD experience

Git and version control

Release management

AWS or Azure experience

Strong software engineering foundation

Herramientas

GitHub Actions

YAML pipelines

CI/CD tooling

AWS

Azure

Descripción del empleo

Globant is seeking an AI Engineer to design, build and deploy agentic AI systems for production. You will architect multi-agent workflows, integrate LLMs and external tools, and ensure reliable operation through prompt engineering and guardrails.

The role requires 5–10 years of software engineering experience, strong Git-based workflows, and hands-on cloud experience with AWS or Azure. You will own delivery timelines and contribute to scalable AI pipelines.