项目狮 - 提示工程师（日本）
Project Lion - Prompt Engineer (Japan)
我们正在寻找一名Prompt Engineer，负责将模板迁移到LLM自动评分器的端到端技术迁移流程。该职位需要使用客户的内部工具，运用提示工程技巧以最大化模型性能。
职责：
利用自动提示生成（APG）工具为复杂的父子模板集群创建基准提示。
运行并监督自动化提示优化（APO）工具，审查输出结果，并在APO遇到死锁或停滞时进行标记。
手动编写、测试和优化提示，以应对复杂的模板架构，克服反模式，并处理工具缺失或故障时的边缘情况。通过设计和优化手动提示来解决边缘情况场景。
监控shadowbot运行，确保有足够的分歧（人类与LLM评分之间的差异）被记录、生成和跟踪。
将提示版本应用于已建立的黄金数据，持续测量自动评分器质量与人类群体基准的对比，计算准确率指标如F1分数、精确率和召回率。
为最终版本撰写技术上线准备理由（上线认证文档）。
要求：
语言能力：日语母语水平，英语流利。
地点：必须在日本工作。
教育背景：计算机科学、数据科学、计算语言学、人机交互（HCI）、认知科学或相关分析领域的学士、硕士或博士学位。
提示工程与AI专业知识：至少4年作为提示工程师的经验。有为严格、结构化输出、复杂分类任务调整大型语言模型（LLMs）的实操经验，并熟悉思维链和少量样本学习。
数据分析：能够识别错误模式，分析模型性能，并熟练使用SQL或其他数据分析工具。
技术敏捷性：具备快速学习并掌握专有工具的能力，且能在最少监督下完成。
沟通能力：出色的口头和书面沟通能力。
可选/优先技能：
熟悉企业级LLM接口，如Goose API。
在AI模型评估、数据科学、计算语言学或软件工程方面有经验。
有自动化提示优化（APO）系统或调优流程的实际操作经验。
语言学专业知识
查看英文原文
We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance.
Responsibilities:
Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters.
Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus.
Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts.
Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked.
Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall.
Draft technical launch readiness justifications (Launch Certification Documentation) for final.
Requirement:
Language Skills: Native fluency in Japanese and fluent in English.
Location: Must be based in Japan.
Education: Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field.
Prompt Engineering & AI Expertise: At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning.
Data Analysis: Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools.
Technical Agility: Ability to quickly learn and master proprietary tools with minimal supervision.
Communication: Excellent verbal and written communication skills.
Optional / Preferred Skills:
Familiarity with enterprise-grade LLM interfaces like the Goose API.
Experience in AI model evaluation, data science, computational linguistics, or software engineering.
Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows.
Linguistic expertise, including an understanding of semantics and logic.