Perfil de habilidad

LLM Deployment

Esta habilidad define expectativas en roles y niveles.

Machine Learning & AI LLM & Generative AI

Roles

donde aparece esta habilidad

Niveles

ruta de crecimiento estructurada

Requisitos obligatorios

los otros 5 opcionales

Machine Learning & AI

LLM & Generative AI

22/2/2026

Selecciona tu nivel actual y compara las expectativas.

Qué se espera en cada nivel

La tabla muestra cómo crece la profundidad desde Junior hasta Principal.

Rol	Obligatorio	Descripción
LLM Engineer		Knows LLM deployment basics: REST API endpoint, model loading, basic serving. Deploys simple inference server on vLLM or text-generation-inference under mentor guidance.

Rol	Obligatorio	Descripción
LLM Engineer		Independently deploys LLM to production: configures vLLM with continuous batching, quantization (GPTQ/AWQ), and health checks. Implements monitoring of latency, throughput, and error rates.

Rol	Obligatorio	Descripción
LLM Engineer		Designs production LLM serving infrastructure: multi-model serving, A/B testing, canary deployments, auto-scaling. Optimizes latency (p50/p95/p99) and throughput under high load.

Rol	Obligatorio	Descripción
LLM Engineer		Defines LLM deployment strategy for the team. Establishes SLA for inference services, monitoring standards, rollback and incident response processes for LLM production systems.

Rol	Obligatorio	Descripción
LLM Engineer		Shapes enterprise LLM serving platform. Defines approaches to multi-model inference at scale, cost optimization, capacity planning, and disaster recovery for critical LLM services.

Junior 1 requisitos

LLM Engineer

Knows LLM deployment basics: REST API endpoint, model loading, basic serving. Deploys simple inference server on vLLM or text-generation-inference under mentor guidance.

Middle 1 requisitos

LLM Engineer

Independently deploys LLM to production: configures vLLM with continuous batching, quantization (GPTQ/AWQ), and health checks. Implements monitoring of latency, throughput, and error rates.

Senior 1 requisitos

LLM Engineer

Designs production LLM serving infrastructure: multi-model serving, A/B testing, canary deployments, auto-scaling. Optimizes latency (p50/p95/p99) and throughput under high load.

Lead / Staff 1 requisitos

LLM Engineer

Defines LLM deployment strategy for the team. Establishes SLA for inference services, monitoring standards, rollback and incident response processes for LLM production systems.

Principal 1 requisitos

LLM Engineer

Shapes enterprise LLM serving platform. Defines approaches to multi-model inference at scale, cost optimization, capacity planning, and disaster recovery for critical LLM services.

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