About the Company/Team

We're building Shafi the first AI‑native cross‑border health platform targeting underserved markets, starting with Arab and adjacent diaspora communities. At the core is a simple but powerful promise: transform paper-based fragmented records into structured consult briefs that help doctors save time and help patients feel heard, and give patients access to high-quality specialists that transcends borders. Our wedge is clear: Arabic‑speaking US doctors, trusted second opinions, and AI‑powered records that make it all possible.

About the Role

This is a founding technical leadership role at Shafi. You’ll be the person who shapes and builds the technology that powers our vision: turning fragmented medical records into clarity and scaling scarce specialist expertise across borders. You’ll work side-by-side with me (MIT EMBA 2027) and my physician cofounder to design and ship our AI-native health platform. It’s a cofounder role, not just a job. you’ll be making architecture choices, building prototypes, experimenting with AI summarization, and helping us scale from MVP to global impact.

We already have 50 Arabic-speaking US based doctors onboarded, an MVP live in the app store, and a pilot underway. We're past the concept stage to building traction and differentiation within the MVP. The technical challenges are hard and exciting: AI summarization of unstructured medical data, secure cross-border health systems, scaling teleconsults. We’re looking for someone who wants to be more than “the coder.” This is about owning the technical vision and being part of the founding story. You don’t need to be a physician but you should be excited about solving big global health problems with AI and data. You should also share our excitement to build a different kind of company and culture. One that is focused on global equity, access, and empowering patients to have a full say in how their data are used. We believe that building trust in the age of AI requires a lot of thoughtful transparency and agency that is often skipped from users, and when it comes to their health data, that is unacceptable