Senior Software Engineer – AI-Driven Platform & Agentic Systems (m/w/d)

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

What We're Looking For

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.

✓

Owners