Skill Profile

LLM Deployment

This skill defines expectations across roles and levels.

Machine Learning & AI LLM & Generative AI

Roles

where this skill appears

Levels

structured growth path

Mandatory requirements

the other 5 optional

Machine Learning & AI

LLM & Generative AI

2/22/2026

Choose your current level and compare expectations. The items below show what to cover to advance to the next level.

What is Expected at Each Level

The table shows how skill depth grows from Junior to Principal. Click a row to see details.

Role	Required	Description
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.

Role	Required	Description
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.

Role	Required	Description
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.

Role	Required	Description
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.

Role	Required	Description
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 requirements

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 requirements

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 requirements

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 requirements

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 requirements

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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