Open Roles

Requirements:

• Hands-on experience with prompt engineering for LLMs in production settings;
• 3+ years of Python development experience (focused on data processing, scripting, simple automation);
• Experience working with US healthcare or clinical data, with an ability to understand and adapt to the variability and complexity of real-world medical documentation;
• Strong understanding of working with unstructured text, PDFs, and scanned documents;
• Exposure to lightweight cloud deployment (e.g., AWS Lambda, EC2, or simple pipelines);
• Experience applying appropriate evaluation frameworks to assess LLM extraction performance in real-world cases;
• Experience with version control (Git with GitHub);
• Familiarity with agile development practices;
• High English level.

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.

Responsibilities:

• Prompt Engineering: Craft and optimize prompts to maximize extraction accuracy across diverse clinical document formats;
• Clinical-Aware Prompt Adaptation: Adapt prompt engineering strategies to account forthe variability, ambiguity, and inconsistency commonly found in real-world healthcare documents;
• Document Classification: Build intelligent workflows to categorize documents by type before extraction (labs, imaging, vaccines, etc.);
• Python Development: Develop robust Python pipelines to interface with LLM services and process extraction outputs;
• Performance Evaluation: Measure and systematically optimize extraction quality across document types and key clinical targets;
• Prompt Adaptability: Adjust prompting strategies as LLM capabilities and frameworks evolve.

About project:

The platform is designed to enhance care coordination, particularly for transplant and chronic disease patients, by enabling more accurate and efficient use of clinical data. It is being scaled across multiple healthcare environments, with a strong emphasis on practical implementation and measurable impact within the US healthcare system.