Eine zielgenaue Bewerbung für diesen Job — ein maßgeschneiderter Lebenslauf und ein Anschreiben, die genau zur Stellenanzeige passen.
virtualQ seeks engineers to build the intelligence layer for enterprise customer communication in production. You will own the intersection of a battle-tested platform and next-gen AI architecture, shipping features that actually run in production for real clients in regulated environments.
Responsibilities include extending backend services, deploying LLM-driven workflows, and building voice agents. A strong focus on architecture, testing, and observability is required, with ownership from day
Build the intelligence layer for enterprise customer communication.
AI-native platform · Real customer contacts · Production, not demos.
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."
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.
You build it, you own it. Here's where you'll have impact:
Extend and improve our backend services and data pipelines — the foundation everything else runs on. Clean architecture, high availability, real scalability.
Bring large language models into real customer workflows: decision logic, tool calling, memory, orchestration. Not wrapped in a demo — shipped and monitored in production.
Build intelligent voice and chat agents for inbound and outbound use cases, including speech recognition, dialogue management, and integration with contact center infrastructure.
Design and implement autonomous workflows — agents that plan, decide, and interact with internal services, embedded in auditable and controllable system boundaries.
Ensure AI-driven features are traceable, testable, and compliant. In regulated environments, explainability and reliability are not nice-to-haves.
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:
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.
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.
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.
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.
A focused engineering team where you work directly with product and leadership. No ticket theater, no layers of approval. Flat hierarchy, honest feedback.