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The Senior AI Engineer will build AI-powered tools to assist healthcare professionals, working on Doctolib Assistant to enhance care delivery and automate tasks.

Lead development and scaling of Customer Operations processes focused on Customer Care. Define KPIs and dashboards, run data-driven analyses, design AI-enabled workflows and automation, drive process improvements, manage budget and capacity planning, and collaborate with stakeholders to improve service quality and customer satisfaction.

Build and operate fullstack interoperability solutions connecting Doctolib to German national health services and EHRs. Design architectures, implement integrations (TI, eRezept, QES, GDT), ensure security, compliance, observability, and partner with cross-functional teams for multi-country rollouts.

Design and train deep learning models that represent patient health across structured records, clinical text, and multimodal signals. Research temporal, causal, calibration, uncertainty, and evaluation methods; publish results; collaborate with data science and product teams to convert research into clinical-grade features, benchmarks, and open-source releases. Help define the lab's research agenda and engage the ML and health communities.

Build and ship backend features for Doctolib's healthcare platform: design robust JVM-based services, drive architectural decisions, integrate partner systems, champion AI-assisted development, promote testing and resiliency, and collaborate across product, design, and engineering teams.

The Senior Software Engineer will design and maintain a Web and Mobile Design System using React and React Native, drive convergence between platforms, ensure accessibility, mentor team members, and improve developer experience through tooling and automation.

The Staff DataOps Engineer will design and implement data infrastructure strategies, optimize data pipelines, and provide technical guidance across teams to enhance data-driven initiatives.

Design, implement, and scale evaluation frameworks and automated pipelines to monitor safety, reliability, and alignment of agentic LLM systems. Define metrics, run experiments assessing reasoning, factuality and robustness, collaborate with model developers and clinicians, and drive iterative improvement and internal knowledge sharing.

Ensure platform reliability, scalability, and observability at European scale. Build and maintain infrastructure-as-code, define SLOs/error budgets, lead cross-cutting reliability initiatives, improve incident detection/response, participate in on-call rotation, and partner with product and engineering teams to embed reliability practices.

Lead platform reliability initiatives at scale: build and maintain IaC and automation, design reliability and observability components, define SLOs/SLIs and alerting, drive incident response and on-call improvements, and partner with product and engineering teams to embed reliability practices across 170+ applications.