Build the intelligence layer for enterprise customer communication.
AI-native platform · Real customer contacts · Production, not demos.
The Problem We're Solving
Customer communication is one of the largest, most fragmented operational challenges in enterprise — and one of the last areas where AI has not yet delivered on its promise. Companies run dozens of disconnected tools for routing, bots, scheduling, and analytics. Customers still wait. Agents still drown.
The intelligence layer is missing.
virtualQ is building that layer. We are the AI-powered operating system for customer communication — a platform that does not bolt on intelligence, but is built on it. Our system processes tens of thousands of real interactions every day across voice and digital channels, for enterprise clients in insurance, healthcare, and public services. Clients who can't afford downtime, and where compliance isn't optional.
"Configured as-a-prompt. Optimized by experience. Trusted by design."
The Role
You'll work at the intersection of a battle-tested production platform and the next generation of AI architecture. That means taking on real ownership — not just shipping features, but shaping how intelligent systems get built and deployed in high-stakes environments.
This is not a research role. It is not a demo team. Every line of code you write runs in production, affects real people trying to reach help, and integrates with the complex infrastructure of regulated enterprises. The bar is high — and so is the impact.
What You'll Own
You build it, you own it. Here's where you'll have impact:
Core Platform Engineering. Extend and improve our backend services and data pipelines — the foundation everything else runs on. Clean architecture, high availability, real scalability.
LLM Integration in Production. Bring large language models into real customer workflows: decision logic, tool calling, memory, orchestration. Not wrapped in a demo — shipped and monitored in production.
Voice & Conversational AI. Build intelligent voice and chat agents for inbound and outbound use cases, including speech recognition, dialogue management, and integration with contact center infrastructure.
Agentic Systems. Design and implement autonomous workflows — agents that plan, decide, and interact with internal services, embedded in auditable and controllable system boundaries.
AI Quality & Observability. Ensure AI-driven features are traceable, testable, and compliant. In regulated environments, explainability and reliability are not nice-to-haves.
The Stack
We are not starting from scratch — and that is a good thing. Our platform is proven in production. We are expanding it deliberately toward AI-native architecture:
Backend
Ruby on Rails · Python · Elixir
Frontend
React · TypeScript · Tailwind · shadcn · Vite
Infrastructure
Cloud native AWS, all-in · Docker
AI & ML
LLM orchestration · Voice AI (STT / TTS / NLU) · ML optimization models
Telco
Deutsche Telekom · Twilio
You bring:
✓ Several years of experience in backend or platform engineering — you've shipped and maintained production systems and know the difference between code that works and code that lasts.
✓ Strong software engineering fundamentals: architecture, testing, observability — not because someone told you to, but because you've felt the pain of the alternative.
✓ Genuine curiosity about — and ideally hands-on experience with — LLMs, conversational AI, or agentic systems. Not just read about it; actually built something.
✓ Ownership mentality. You take on a problem, drive it forward, and flag issues early. You don't wait to be asked.
✓ A permanent work and residency permit for Germany / EU.
Bonus points if you have:
- German language skills – that might be helpful during building great prompts
- Experience with voice systems, bots, or dialog platforms in production
- Familiarity with LLM frameworks (LangChain, LlamaIndex, or similar) or agentic patterns
- Understanding of enterprise security requirements: ISO 27001, GDPR, audit trails
Why virtualQ - Why Now?
Production-grade AI, not a lab. The infrastructure you build serves tens of thousands of real interactions for clients who can't switch off. That makes the engineering harder — and the impact real.
Greenfield on Brownfield. A mature, stable platform paired with wide-open architectural decisions on the path to AI-native. High ownership. Actual say in how things get built.
The experience flywheel. We've accumulated real-world experience over a large number of contact center deployments and use cases. That knowledge makes our models better with every new client — a compounding advantage no new entrant can replicate quickly.
Trusted by design — Made in Europe. ISO 27001 certified, GDPR-native, built for heavily regulated industries. As data sovereignty becomes strategically critical, this is a differentiator, not just a compliance checkbox.
Small team. Real ownership. A focused engineering team where you work directly with product and leadership. No ticket theater, no layers of approval. Flat hierarchy, honest feedback.
How We Hire
We keep it straightforward and respectful of your time:
1 - Intro call (45 min)
A quick conversation with engineering leadership — no trick questions, just context.
2 - Technical conversation pt. 1 (60 min)
We talk through something you've built. Your time to shine.
3 - Technical conversation pt. 2 (60-90 min)
We talk through something you’ve fixed for us ;-) Your chance to shine even more!
4 - Founder conversation (45 min)
A brief conversation with one of our founders – again, no trick questions, just cultural fit.
5 - Offer
Fast feedback. We don't let decisions sit.
Send us what you've built — a GitHub profile, a project, a system you're proud of. No cover letter required. We'll get back to you within 48 hours.
