- Company Name
- MAGE-X Medical AI
- Job Title
- CTO / Head of Engineering (Data & IA)
- Job Description
-
**Job title**
CTO / Head of Engineering (Data & AI)
**Role Summary**
Lead the technology strategy, architecture, and delivery of a medical data intelligence platform. Collaborate with executive leadership and clinicians to transform a product roadmap into a scalable, compliant, and high‑quality AI/ML solution for the health‑tech sector.
**Expectations**
- Own the long‑term technology vision and ensure alignment with business goals.
- Deliver a robust, privacy‑first, GDPR/HDS‑compliant architecture for handling sensitive medical data.
- Scale infrastructure, optimize LLM pipelines, and maintain scientific reproducibility.
- Guide regulatory submissions (MDR, CE, ISO) and maintain rigorous documentation.
- Build, mentor, and expand a high‑performance engineering and data science team.
**Key Responsibilities**
1. Define and evolve the HDS‑compliant platform architecture (servers, databases, LLM hosting).
2. Design a modular, scalable AI stack that is LLM‑agnostic.
3. Implement privacy‑by‑design, RGPD, HDS standards across all products.
4. Lead the development of NLP pipelines, prompt engineering, model selection, and few‑shot learning.
5. Create the Golden Dataset in partnership with clinical experts and ensure data quality.
6. Oversee algorithmic performance, scientific validation, and reproducibility.
7. Coordinate MDR/CE, ISO, and patent documentation, ensuring compliance with EU medical device regulations.
8. Drive strategic partnerships with hospitals, researchers, and investors.
9. Recruit and retain core technical talent; establish best practices and dev‑ops pipelines.
10. Represent the technology function during fundraising, audits, and stakeholder meetings.
**Required Skills**
- 5+ years in software, data, and AI engineering.
- Deep knowledge of LLMs, NLP pipelines, and evaluation frameworks.
- Experience building complex SaaS or deep‑data products in regulated environments (health‑tech, fintech, etc.).
- Proven ability to architect and launch end‑to‑end solutions from scratch.
- Familiarity with cloud platforms (AWS, GCP, OVH) and MLOps best practices.
- Strong leadership, communication, and stakeholder‑management skills.
- Product‑oriented mindset with a passion for quality and continuous improvement.
- Comfortable engaging with clinical professionals and translating medical concepts into technical solutions.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Certifications in MLOps, cloud architecture, or data engineering are a plus.