Project Lion - Prompt Engineer - United States (Remote, Part-Time)

Remote; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

Remote is seeking a Prompt Engineer based in the United States to own the end-to-end migration workflow for transitioning templates to LLM autoraters. You will leverage internal tools to optimize prompts and maximize model performance.

The role requires 2+ years of experience, native English, and strong data-analytics skills. You will collaborate across teams and contribute to launch readiness documentation.

Qualifications

• Native fluency in English.
• Based in United States.
• 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.
• At least 2 years' experience as Prompt Engineer.
• Proficient in SQL or other data analytics tools.
• Ability to quickly learn and master proprietary tools with minimal supervision.
• Excellent verbal and written communication skills.

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 outputs, and flag when APO reaches deadlocks or plateaus.
• Manually draft, test, and refine prompts to navigate complex template architectures and handle edge cases.
• Monitor shadowbot runs to ensure disagreements between human and LLM ratings are tracked.
• Run prompt versions against gold data to measure autorater quality against human baseline (F1, precision, recall).
• Draft technical launch readiness justifications (Launch Certification Documentation) for final.

Skills

Prompt engineering

LLM tuning

Data analysis

Communication

Education

Bachelor’s/Master’s/Doctorate in CS/DS/Computational Linguistics/HCI/Cognitive Science

Tools

SQL

Goose API

Job description

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 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.

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.