Our client is building the infrastructure behind the next generation of voice-first AI, redefining how people and machines interact in real time. Backed by over €190m in funding and valued at more than €890m, they’re tackling one of the most exciting design challenges of the decade: making complex AI systems feel effortless, intuitive, and unmistakably human.

Their distributed platform enables millions of real-time interactions each year - from AI-driven systems handling over 3 million customer requests annually to intelligent assistants supporting more than 500,000 complex user journeys for some of the world’s most recognisable brands.

Role Overview:

The AI Engineering Manager will lead a team of machine learning, backend, and data engineers focused on building multilingual voice infrastructure from scratch. This includes everything from automatic speech recognition (ASR) and text-to-speech (TTS) to language detection, acoustic echo cancellation, and real-time orchestration of ML models in production.

Key Responsibilities:

* Lead and grow a high-performing team of ML, backend, and data engineers, fostering collaboration and technical excellence.

* Oversee the development, fine-tuning, and productionisation of ASR, TTS, language detection, and audio processing models.

* Ensure scalable customisation of speech models across languages and client use cases.

* Own orchestration services critical to real-time ML performance and reliability.

* Work cross-functionally with product, platform, and AI research teams to align technical efforts with company strategy.

* Coach and support team members, developing a culture of continuous learning and innovation.

Qualifications:

* Strong professional background in ML engineering or data science.

* People management experience, including leading ML-focused teams.

* Proven experience in developing production-grade ML models, including monitoring, scaling, and lifecycle management.

* Deep understanding of building and maintaining real-time ML services, ideally in cloud-native environments.

* Strong track record of implementing engineering and ML best practices.

If you’re excited about leading a team shaping the multilingual voice layer of next-gen AI - and turning technical complexity into scalable, human-centric products, we’d love to hear from you.