Project Lion - 提示工程师 - 美国（远程，兼职）
Project Lion - Prompt Engineer - United States (Remote, Part-Time)
我们正在寻找一名Prompt Engineer，负责将模板迁移至LLM自动评分系统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。
联邦法律合规
根据联邦法律，所有被聘人员将需要：
- 验证身份及在美国工作的资格；以及
- 完成必要的雇佣资格验证表格。
请注意，根据联邦法律（I-9流程）要求核实工作授权，所有新员工必须在入职前三天内通过视频实时验证，并提供所选身份证件的照片。
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职责：
- 使用自动提示生成（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出现死锁或停滞时进行标记。
- 手动撰写、测试和优化提示，以应对复杂的模板架构，克服反模式，并处理工具缺失或失效时的边缘情况。通过设计和优化手动提示来解决边缘案例场景。
- 监控shadowbot运行，确保足够的分歧（人类与LLM评分之间的差异）被记录、生成并跟踪。
- 将提示版本应用于已建立的黄金数据，持续评估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。
- 编写最终的技术上线准备理由（上线认证文档）。
要求：
- 语言技能：英语母语水平。
- 地点：必须位于美国。
- 教育：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2年作为提示工程师的经验。有为严格、结构化输出调整大型语言模型（LLMs）的实操经验，熟悉复杂分类任务，以及思维链和少量样本学习。
- 数据分析：具备识别错误模式、分析模型性能的能力，并熟练使用SQL或其他数据分析工具。
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.
Federal Law Compliance
In compliance with federal law, all persons hired will be required to:
- Verify identity and eligibility to work in the United States; and
- Complete a required employment eligibility verification form.
Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
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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 English.
- Location: Must be based in United States.
- 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 2 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.