Build the internal operating system for modern rehabilitation.

nyra health builds AI-powered rehabilitation software used in over 100 clinics across Germany and Austria. We've raised €20M in Series A funding and are scaling fast — expanding across DACH and preparing for the US market.

We have a proven product, clinical validation, and insurance reimbursement. Now we want to build the internal systems to match.

Our ambition is to operate as close to company as code as possible — where repetitive work is automated by default, not by exception, and people spend their time on the things that actually matter.

That's where you come in.

We're hiring an AI Engineer to help build the workflows, agents, and internal tools that make nyra faster, smarter, and more scalable — and to contribute to applied LLM work across our product.

You'll work across commercial, operations, customer success, product, clinical, finance, and people workflows — identifying bottlenecks, reducing manual work, and turning messy processes into systems. As part of the Machine Learning team, you'll also support in the design, implementation and improvement of the AI-driven features in our product.

Your main focus will be automating high-leverage internal workflows and helping nyra become an AI-native organization.

You'll combine hands-on automation skills, strong technical judgment, and a sharp eye for process design to create real business impact.

RESPONSIBILITIES

Workflow automation & internal systems

Design, build, and maintain automations across the company Connect our core tools and data across teams Reduce repetitive manual work and improve operational reliability Take workflows from design through rollout, including monitoring, documentation, and failure handling

AI deployment & applied LLM work

Help identify high-value use cases for LLMs, copilots, and AI-assisted workflows Build internal AI tools for summarization, drafting, triage, QA, and knowledge access Contribute to applied LLM work in our product — iterating on prompts for exercises, implementing the backend of AI-driven features, and designing tests and evals to make sure LLMs behave as expected Know when AI is the right answer — and when standard automation is better

AI evangelism & capability building

Stay up to date with the fast-moving AI tooling landscape Be someone teammates across the company can come to with AI questions Contribute to internal workshops, demos, and enablement materials Help create repeatable playbooks, examples, and best practices that drive adoption

Process improvement & scale

Partner with teams to understand pain points and redesign workflows Translate operational problems into robust systems Track impact through time saved, cycle time reduction, throughput, and error reduction Improve workflows continuously as the company scales

Reliability, privacy & trust

Build with safeguards, auditability, and resilience in mind Handle sensitive data responsibly Help apply practical guardrails for internal AI usage Partner with engineering and ML to ensure systems scale well

Must-haves

Automation experience — You've built production workflows, integrations, or internal tools that people actually use

AI fluency — You're comfortable with LLMs, Claude Code, OpenAI Codex, prompting, agent workflows, retrieval, and evaluation

Strong builder mindset — You think in systems, edge cases, maintainability, and scale

Evangelist mindset — You enjoy learning new tools, sharing what you find, and helping others adopt better ways of working

Impact orientation — You care about real outcomes, not just shipping automations

Cross-functional communication — You work well with technical and non-technical stakeholders

Ownership — You can drive individual projects from idea to rollout in a fast-moving environment

Nice-to-haves

Experience in healthtech, digital health, or another regulated environment

Familiarity with Python, TypeScript, SQL, APIs, and modern SaaS tooling

Experience working with privacy-conscious systems and sensitive data

Experience building internal tooling in a high-growth startup

Experience shipping reliable LLM-powered features

The Process

• Intro call (~30 mins): Background, expectations, and an overview of nyra health and the role.
• Technical interview: A practical session with the Android team where you share a personal project and discuss software implementation and technical details.
• Meet with Founders: Discuss your approach, technical philosophy, and how you'd contribute to building the future of neurotherapy on Android.