About the role
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 Dutch and fluent in English.
-
Location: Must be based in Netherlands.
-
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.