AI Engineer — Automation & Internal Systems

nyra health builds the digital tools that make neurological rehabilitation work inside and outside clinic walls: myReha, the patient therapy app, and nyra insights, the clinician platform. 100+ clinics, 100K+ patients across DACH. 3× MRR growth target for 2026. €20M Series A. Scaling the team to around 50 this year. Ownership, excellence and patients first — that’s how we drive progress together. Nachfolgend finden Sie eine vollständige Aufschlüsselung aller Anforderungen an potenzielle Bewerber sowie eine Anleitung zur Bewerbung Viel Glück. We’re well on our way to becoming AI-native, but there is still so much more we can do with work automation. You’ll help us unlock it, one workflow at a time. Our ambition is company as code: our processes live as code, our agents do the repetitive work, and every colleague knows how to work with AI. Together with our AI Automation team, you’ll make that real across the company. We’re hiring an AI Engineer to join our AI Automation team. You’ll build the workflows, agents and internal systems that help colleagues work more effectively. The role combines process design, hands‑on automation and the cloud and data foundations that make those systems reliable. You’ll shape the automation roadmap: you find where time is lost, decide what’s worth building, and ship it into daily use. You’ll work directly with colleagues across commercial, operations, product, clinical, finance and people. What you’ll work on Understand and improve how nyra works Map how teams work: their processes, systems, responsibilities and handoffs. Build a shared process map that colleagues can use and keep up to date. Find improvements and automation opportunities, and agree on priorities, scope and expected benefits with the people doing the work. Build automations people can rely on Build and ship workflows, integrations and internal tools with AI coding agents as your default. Guide agents with clear context and reusable skills, review their changes, and verify results through tests and evaluations. Own rollout and reliable operation, including cloud infrastructure, deployments, access controls, monitoring and recovery when something fails. Choose the right mix of AI, conventional integrations and process changes for each problem. Help colleagues work well with AI Turn proven AI‑assisted workflows into reusable agent skills, practical examples and documentation that colleagues can use in their daily work. Help technical and non‑technical colleagues adopt AI through hands‑on support, demos and short workshops. Evaluate what improves speed, quality or reliability and share what works. What you bring AI-native development: Coding agents (Claude Code, Codex, Cursor or similar) are already your default way of building, and you can show us what you’ve shipped this way. You know how to structure tasks, supply the right context and tools, and evaluate and improve the results. Engineering judgment: You understand code, system design and data flows, can assess changes generated by AI, and can investigate failures across connected systems. You are comfortable working with Python or TypeScript. Production delivery: You’ve shipped and maintained automations, integrations or internal tools that people use. You can deploy them and keep them reliable through testing, monitoring and failure handling. Cloud