Role overview
- Our solutions are built on a single, fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to the country and healthcare specialty requirements. To address these challenges, we are modularizing our platform run in a distributed architecture through reusable components.
- Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
- We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here!
What you'll work on
- Design, ship, and operate production-grade agentic LLM systems that improve patient-practitioner interaction and streamline healthcare workflows
- Validate hypothesis with offline evaluation datasets and A/B tests on real traffic
- Partner with other machine learning teams to design and improve evaluation pipelines, security/safety guardrails, and metrics
- Develop and maintain core agentic capabilities, including memory, reasoning orchestration, and tool adapters, ensuring strong observability, fallback mechanisms, and fail-safe behaviors
- Own performance, observability, and security: monitoring dashboards, SLO/SLI, security posture
- Ensure privacy and security by design
- Contribute to cross-functional initiatives that shape Doctolib's future AI platform and best practices in building agentic systems that will reinvent the work of health professionals and improve people's health
Interview process
- Recruiter Interview
- Feature Building Interview
- AI System Design Interview
- Behavioral Interview
- Reference check
- Offer!
Tags & focus areas
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