技能档案

LLM Prompt Engineering

此技能定义了各角色和级别的期望。

Machine Learning & AI LLM & Generative AI

角色数

包含此技能的角色

级别数

结构化成长路径

必要要求

其余 10 个可选

Machine Learning & AI

LLM & Generative AI

2026/2/22

选择当前级别并对比期望。下方卡片显示晋升所需掌握的内容。

各级别期望

表格展示从初级到首席的技能深度变化。点击行查看详情。

角色	必要性	描述
Data Scientist		Creates basic prompts for LLM: structured queries for data analysis, code generation, information extraction. Understands zero-shot and few-shot prompting principles. Iteratively improves prompts based on model response quality.
LLM Engineer		Knows basic prompt engineering techniques: zero-shot, few-shot, chain-of-thought. Creates simple prompts for classification and text generation tasks, tests variations under mentor guidance.

角色	必要性	描述
Data Scientist		Applies advanced prompting techniques for data science tasks: chain-of-thought, self-consistency, ReAct. Designs prompt pipelines for analytics automation. Evaluates prompt quality through systematic benchmarking on test sets.
LLM Engineer		Independently develops complex prompt templates: structured output, tool use, multi-step reasoning. Conducts systematic prompt optimization with A/B testing and quality metrics.

角色	必要性	描述
Data Scientist		Designs production prompt engineering systems for scalable LLM applications. Applies prompt optimization, automatic prompt tuning. Builds prompt testing frameworks with regression testing and quality monitoring for production.
LLM Engineer		Designs production prompt engineering systems: prompt versioning, automated optimization, meta-prompting. Implements dynamic prompt construction based on context and user intent.

角色	必要性	描述
Data Scientist		Defines prompt engineering strategy for the data science team. Establishes shared prompt library and best practices. Coordinates prompt development workflow with version control and collaborative review.
LLM Engineer		Defines prompt engineering standards for the LLM team. Establishes prompt libraries, prompt testing guidelines, review processes. Coordinates prompt optimization for production systems.

角色	必要性	描述
Data Scientist		Shapes prompt engineering strategy at organizational level. Defines governance model for prompts: security, cost optimization, quality standards. Evaluates prompting paradigm evolution and prepares the organization for changes.
LLM Engineer		Shapes enterprise prompt engineering strategy. Defines approaches to centralized prompt management, automated prompt optimization, and prompt quality at organizational scale.

Junior 2 要求

Data Scientist

Creates basic prompts for LLM: structured queries for data analysis, code generation, information extraction. Understands zero-shot and few-shot prompting principles. Iteratively improves prompts based on model response quality.
LLM Engineer

Knows basic prompt engineering techniques: zero-shot, few-shot, chain-of-thought. Creates simple prompts for classification and text generation tasks, tests variations under mentor guidance.

Middle 2 要求

Data Scientist

Applies advanced prompting techniques for data science tasks: chain-of-thought, self-consistency, ReAct. Designs prompt pipelines for analytics automation. Evaluates prompt quality through systematic benchmarking on test sets.
LLM Engineer

Independently develops complex prompt templates: structured output, tool use, multi-step reasoning. Conducts systematic prompt optimization with A/B testing and quality metrics.

Senior 2 要求

Data Scientist

Designs production prompt engineering systems for scalable LLM applications. Applies prompt optimization, automatic prompt tuning. Builds prompt testing frameworks with regression testing and quality monitoring for production.
LLM Engineer

Designs production prompt engineering systems: prompt versioning, automated optimization, meta-prompting. Implements dynamic prompt construction based on context and user intent.

Lead / Staff 2 要求

Data Scientist

Defines prompt engineering strategy for the data science team. Establishes shared prompt library and best practices. Coordinates prompt development workflow with version control and collaborative review.
LLM Engineer

Defines prompt engineering standards for the LLM team. Establishes prompt libraries, prompt testing guidelines, review processes. Coordinates prompt optimization for production systems.

Principal 2 要求

Data Scientist

Shapes prompt engineering strategy at organizational level. Defines governance model for prompts: security, cost optimization, quality standards. Evaluates prompting paradigm evolution and prepares the organization for changes.
LLM Engineer

Shapes enterprise prompt engineering strategy. Defines approaches to centralized prompt management, automated prompt optimization, and prompt quality at organizational scale.

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