LLM Prompt Engineer

We are seeking a highly skilled LLM Prompt Engineer to design, optimize, and evaluate interactions with large language models (LLMs). This role is ideal for someone who excels at crafting clear, precise prompts, understands how to influence model behavior, and can collaborate closely with technical and non-technical stakeholders. 
The ideal candidate will have experience working with healthcare-related text data and strong English communication abilities.
 

    We offer:

• Flexible working hours;
• Paid vacation and sick days;
• Health insurance;
• Professional growth;
• Internal English classes and compensation for educational courses;
• Professional accountant and lawyer;

• Friendly atmosphere.

  
  Requirements

• 1–3+ years of experience in prompt engineering, NLP, machine learning, or similar fields.
• Strong command of English with exceptional writing clarity and style.
• Proficiency in Python, including ability to manipulate text, call LLM APIs, and build evaluation scripts.
• Demonstrated ability to design prompts that improve accuracy, reliability, and interpretability of LLM outputs.
• Experience handling unstructured text, especially clinical or technical content.

• Bachelor’s degree in a relevant field (e.g., Computer Science, Linguistics, Cognitive Science, Data Science, Engineering, or related disciplines).

  
  Will be a plus: 

• Experience working with healthcare notes, EHR/EMR data, clinical terminology, or medical workflows.
• Familiarity with LLM evaluation methodologies (e.g., human evaluation, rubric-based grading, automated scoring).
• Knowledge of RAG systems, vector databases, or fine-tuning workflows.
• Understanding of data privacy, PHI handling, and compliance standards.

• Experience with analytics libraries (Pandas, NumPy) or model-related tooling.

  
  Responsibilities

• Develop, test, and refine prompts to improve LLM performance across various use cases.
• Analyze model outputs to identify improvement opportunities and implement iterative prompt enhancements.
• Collaborate with product, engineering, clinical, and research teams to translate complex requirements into high-quality prompt strategies.
• Document prompt libraries, style guidelines, evaluation metrics, and best practices.
• Ensure prompt designs comply with security, privacy, and healthcare regulatory requirements (e.g., HIPAA) when applicable.
• Assist in the development of fine-tuning datasets, synthetic data generation processes, and domain-specific evaluation sets.