StellDirVor is an independent consulting, trade and technology company specializing in immersive technologies for healthcare. We support organizations in implementing digital innovations — Virtual, Augmented, and Mixed Reality as well as AI — particularly for learning, training, and real-time assistance in clinical and care environments. By combining technology and healthcare, we help optimize processes, improve knowledge transfer, and enhance quality of care.

Supported by a Germany (ZIM) and Taiwanese (GIPIP) partnership grant, we are currently developing ARAIAS — an AR- and AI-based hands-free training and assistance system for chronic wound care. Using AR smart glasses, the system enables 3D wound capture, AI-supported analysis, and standardized remote expertise and documentation directly at the point of care. ARAIAS introduces a new approach to hands-on, safe, and evidence-based learning and training in clinical settings, with the long-term goal of reducing workload for healthcare professionals and improving care outcomes.

We're at an early and exciting stage — moving from concept to working prototype. The near-term focus is on validating the AI models, establishing the core technical foundations, and building toward a proof of concept we can test in real education and clinical settings. As the project matures, the work will naturally evolve from experimentation and prototyping into more structured development and productionization.

Notes:

Location for this role: Remote (within Germany) - due to the nature of the project, we can only consider candidates who are already residing in Germany.

Tasks

Design and build the back-end infrastructure — REST APIs, cloud services, and data pipelines that connect all system components
Build and manage system integrations — connecting hardware, external services, and internal components into a cohesive and reliable data flow
Implement real-time data streaming — from smartglass sensor capture through to server-side processing and response delivery back to the device
Integrate AI capabilities into the application layer — including language understanding, audio processing, and output validation and scoring pipelines
Interface with smartglass SDKs and sensor APIs to establish device-to-back-end data pipelines, working from technical documentation provided by our hardware partner
Connect AI model outputs into application layers — inference endpoints, model versioning, and performance monitoring
Support computer vision — from architecture development and integration — connecting CV model outputs into the back-end and application layer
Make pragmatic architectural decisions appropriate for the current prototyping stage
Set up CI/CD, containerization, and basic observability to keep the team moving fast
Support integration points between the back-end and Unity-based front-end (nice to have)

Requirements

Must-Have

Back-end engineering proficiency — REST API design, system integration, and data pipeline development with Python as the primary language (FastAPI or equivalent)
Real-time integration experience — building streaming pipelines, WebSocket communication, or similar low-latency data flows between devices and servers
AI engineering experience — hands-on integration of AI models and services into production or prototype systems, spanning language understanding, audio processing, and output validation and scoring workflows
System integration experience — connecting hardware, third-party APIs, and internal services across different layers into a coherent, functioning system
Cloud platform experience (AWS / GCP / Azure) — able to spin up infrastructure, manage storage, and deploy services independently
Comfort working with hardware SDKs and APIs — able to independently navigate technical documentation and integration guides to establish device-to-server data flows
Comfortable with Docker and basic CI/CD pipelines
Self-directed and pragmatic — able to take initiative, own problems end-to-end, and make sensible technical decisions independently in a lean team
Fluent in English — German is a bonus

Strong Plus

Database experience — PostgreSQL, NoSQL, object storage (S3 / GCS)
Unity experience or familiarity with Unity's integration patterns
Familiarity with semi-supervised learning — leveraging limited or partially labeled data, relevant when annotated wound imaging data is scarce
Experience with 3D data pre-processing and post-processing — depth map handling, point cloud cleaning, mesh reconstruction, or similar.
Exposure to multi-modal learning — combining RGB and depth or LiDAR data into unified model inputs

Benefits

Meaningful work — You help shape how technology redefines education and training in healthcare, with real impact on clinical outcomes
Ownership and creative freedom — You work autonomously, contribute your ideas directly, and have a genuine say in how the system is built
A learning culture — We support personal and professional growth through knowledge sharing, access to innovative tools and methods, and a dedicated learning budget
Flexible working — Remote-friendly setup with the option to work from our Munich office
Flat hierarchies and team spirit — A small, open, and trust-based team where communication is direct and everyone's voice matters
International collaboration — Work alongside a Taiwan-based partner covering technology, hardware, and research
Due to the nature of the project, we can only consider candidates who are already residing in Germany.
We are only able to respond to candidates selected for further consideration. If you have not heard from us within four weeks of applying, please consider your application unsuccessful at this time.

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