Principal AI Systems Architect & Production ML Leader

team.blue; Toscana; On-site; EUR 120,000 - 180,000; Full time

Job summary

team.blue is building the AI layer that runs across one of Europe’s largest digital-services ecosystems, powering hosting, domains, email, and SaaS for millions of SMBs. As Principal AI Solutions Engineer you will be the senior technical authority on AI systems end-to-end—research, fine-tuning, orchestration, real-time inference, and production reliability.

This role is not purely research or MLOps; you will set technical direction, ship production AI, and raise the bar across a fast-moving team

Qualifications

• ,

Responsibilities

• Architect and evolve the multi-agent orchestration platform (Hermes/Multica), including plugin systems and tool-use pipelines.
• Design and implement voice AI pipelines - STT, real-time TTS, VAD, and SIP/RTP integration with sub-300 ms latency targets.
• Build and maintain RAG pipelines with retrieval quality measurement, re-ranking, and hybrid search over vector + keyword indexes.
• Define MCP server architecture and tool-use contracts across internal and third-party integrations.
• Fine-tune and evaluate LLMs (LoRA, QLoRA, DPO) for domain-specific tasks including customer support and classification.
• Manage model lifecycle: experiment tracking, versioning, reproducibility, and promotion to production.
• Own the AI observability stack: Langfuse tracing and cost tracking; enforce guardrails against hallucination and data leakage.

Skills

LLM production

Fine-tuning

Agentic AI

Python

PyTorch

Transformers

PEFT/LoRA

RAG

Langfuse

Observability

CI/CD for ML

Docker/Kubernetes

Speech AI

Tools

Hermes

Multica

VibeVoice

Silero

SIP/RTP

Langfuse

TensorRT-LLM

vLLM

Docker

Kubernetes

Job description

team.blue is building the AI layer that runs across one of Europe’s largest digital-services ecosystems, powering hosting, domains, email, and SaaS for millions of SMBs. As Principal AI Solutions Engineer you will be the senior technical authority on AI systems end-to-end—research, fine-tuning, orchestration, real-time inference, and production reliability.

This role is not purely research or MLOps; you will set technical direction, ship production AI, and raise the bar across a fast-moving team