Principal AI Engineer

Principal/Founding AI Engineer specializing in Agentic GenAI & Medical Data

Company Overview

Join a rapidly growing medical-tech startup, backed by $75M in funding, building a 3-sided marketplace transforming how healthcare connects, transacts, and personalizes patient experiences. We’re a product-led, remote-friendly team with engineering and commercial operations in the US and Croatia.

Role Overview

As a Senior Software Engineer, you’ll architect and develop agentic GenAI workflows leveraging Python, Django, and cutting-edge AI/ML tools. You will be responsible for designing internal platforms built on sensitive medical datasets, deploying market-facing solutions, and collaborating closely with commercial and AI teams to iterate rapidly.

Key Responsibilities

• Build agentic GenAI workflows using proprietary and medical datasets.
• Lead GenAI & workflow orchestration for healthcare data and knowledge management.
• Develop and optimize marketing technology: email delivery, user engagement, personalization solutions, and growth engineering initiatives.
• Prototype, productize, and validate commercial AI models—understand and model clinician behavior, prescription workflows, and intelligent decision systems.
• Write production code for backend (Python/Django), ensure robust system architecture, and lead technical implementation cycles.
• Partner with cross-functional teams across the US and Croatia to deliver rapid, validated product iterations.

Skills & Experience

• Proven backend expertise: Python and Django in production environments.
• Frontend experience: React (modern best practices).
• Cloud/infrastructure: AWS (deploying, scaling, monitoring).
• Databases: PostgreSQL; ability to optimize for large medical/structured datasets.
• AI/ML: Experience with OpenAI and agent knowledge systems strongly preferred. Track record training or managing AI agents a plus.
• Nice-to-have: Direct experience handling medical/healthcare data.
• Scalability: Experience architecting knowledge systems with large-volume data indexing, not high-throughput but focused on effective information retrieval.