About the Role
<p><strong>Who are we?<br><br></strong></p><p>Recare is one of the leading digital startups in the German healthcare industry and has set itself the task of rethinking healthcare with a platform for digital care coordination. We search, find and coordinate capacities so that the healthcare actors have more time for their patients.<br></p><p>Within a very short time, Recare was able to gather around 75 percent of German acute hospitals as well as more than 26,000 care and rehabilitation facilities on its digital platform. Renowned hospitals and hospital groups such as Vivantes, Sana Kliniken AG, München Klinik, Hannover Medical School and Essen University Hospital are among Recare’s customers and use the Recare platform.<br></p><p>We believe artificial intelligence will transform healthcare more profoundly than any technology since the internet, and we’re building that future today, not tomorrow. While the German healthcare sector has historically focused on the risks of new technologies, we see an unprecedented opportunity to solve the industry’s most pressing challenges with AI. With most German acute hospitals now using the Recare platform, we take our leadership responsibility seriously: we’re helping clinics achieve what once seemed impossible, from automation of administrative workflows with the Recare AI platform to unlocking billions in value through predictive analytics. The potential is real, the technology is ready, and the time is now.<br><br></p><p><strong>Role & team summary<br><br></strong></p><p>As a senior member of the AI team, you will work on building cutting-edge agentic systems that work reliably in production environments where privacy and correctness are top priorities. This is a hands-on role: you will own key AI initiatives end to end and work across products, since the hardest problems here span more than one team.</p><p>Our team is small but growing fast; we are highly independent and hold ourselves accountable for the quality of our work. Technical excellence is expected, but our ideal colleague shares our passion for building impactful solutions that make it all the way into production. As one of our most experienced engineers, you will mentor others, help shape our AI technical strategy, and work with product and business stakeholders to turn open questions into clear recommendations. We want to improve society, not just brag about building fancy tech!<br><br></p><p><strong>What you’ll work on<br><br></strong></p><ul><li><p><strong>Agentic applications:</strong> Build robust chat and generative AI applications on agentic frameworks, designing and optimizing core agent behavior: routing, tool calls, context management, grounding, and instruction-following. Every output is a draft until a clinician releases it, and the system is built for that.</p></li><li><p><strong>Evaluation:</strong> Measure the real value of agentic systems through observability data, custom evaluation metrics, and user feedback, and use those results to improve prompts, models, and system design.</p></li><li><p><strong>GenAI observability:</strong> Set up and improve logging, tracing, metrics, dashboards, and prompt management for our AI systems.</p></li><li><p><strong>Deployment and integration:</strong> Develop and maintain the infrastructure that ships AI agents into REST APIs and web UIs, including containerization, orchestration, and API development.</p></li><li><p><strong>Safeguarding health data:</strong> Embed security best practices and uphold compliance to protect sensitive health information.</p></li><li><p><strong>Technical direction:</strong> Track new AI developments, turn the promising ones into production-ready implementations, and help set the direction of our AI work.</p></li></ul><p style="min-height: 1.7em;"></p> <br> <p><strong>What we’re looking for<br><br></strong></p><ul><li><p>8+ years of relevant industry experience, with a strong AI/ML background, at senior level or above.</p></li><li><p>Hands-on experience designing, shipping, and operating LLM-powered products (RAG, agents) in live production. Research projects and prototypes alone aren’t enough here; we want to hear about systems real users depended on. If your background is in productionizing traditional ML systems rather than LLMs, we still want to hear from you.</p></li><li><p>Hands-on experience with LLM evaluation, such as golden datasets, LLM-as-a-judge, or offline and online metrics, and with systematically improving prompts and models.</p></li><li><p>Solid deep learning experience applied to real-world problems, with a focus on system-level integration rather than model training alone.</p></li><li><p>Strong coding skills across the stack. Ours includes Python, Go, GitHub Actions, and AWS, and you’re comfortable reading and fixing code outside the main codebase.</p></li><li><p>Proficiency in Python and at least one web framework (FastAPI, Django, Flask, …).</p></li><li><p>Experience in environments where security and