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.

Compensation

Additional Information