Lead Prompt Engineer

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: 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 7 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.