EU remote
Backend & Applied AI Engineer
About this role
🏨 The Company Resilience Care, a leading player in remote medical monitoring and a partner in clinical research, is a French company founded in 2021 with a single mission: to provide better care. Our company offers remote monitoring solutions in oncology, gastroenterology and psychiatry, based on the collection of ePROs combined with AI technologies. These solutions rely on a monitoring platform for healthcare professionals—enabling the early detection of side effects for continuous and proactive care—and a mobile app for patients, empowering them to measure and manage their symptoms using tailored resources.
Our solutions optimise patient care, continuously enrich our understanding of patients throughout their healthcare journey and accelerate clinical research through the collection, structuring and in-depth analysis of real-world data. 📝 Your Role In a nutshell You will join our engineering team as a Backend & Applied AI Engineer. Your role will focus primarily on a product used to structure real-world clinical data: developing and maintaining product services and APIs, improving performance and architecture, and strengthening production reliability.
You will also contribute to the delivery of AI-enabled features through code review and backend integration. In the short and medium term, the role is expected to be approximately 75% backend and 25% Applied AI. This split may evolve with team and product needs, without a predefined trajectory. Your impact Become progressively autonomous on the product backend during your first six months. Reduce production blind spots by improving incident detection and follow-through.
Evolve the architecture to better support concurrency, parallelism and processing volumes. Help the team deliver AI components that are reliable, performant and properly integrated into the product. Your day-to-day work Develop and maintain backend services and APIs in Python. Work with the rest of the team, to deliver product changes end to end. Measure and improve processing time, scalability and backend architecture.
Strengthen testing, CI/CD, observability and production reliability. Collaborate with, the Applied AI Engineer, particularly on pull-request reviews and the backend integration of AI-enabled features. ✨ Your Team You will work closely with: Ivan Panico — Lead ML Engineer and your manager , who will support your ramp-up and major architectural decisions. Tom — Applied AI Engineer , who owns the main Applied AI topics and partners with you on product integration.