# team.blue — Principal AI Solutions Engineer

| Field | Value |
|---|---|
| **Date found** | 2026-05-30 |
| **Company** | team.blue |
| **Role** | Principal AI Solutions Engineer |
| **Location** | Dublin, Ireland (Remote) |
| **Salary** | Undisclosed |
| **Job URL** | [LinkedIn](https://www.linkedin.com/jobs/view/4420913655/) |
| **Status** | New |

---

## Company Research

| Field | Value |
|---|---|
| **Headquarters** | Netherlands (Amsterdam area) |
| **Founded** | 2018 (as combined entity) |
| **Employees** | 3,000+ employees; 3,390 on LinkedIn (883 active) |
| **LinkedIn** | [team.blue](https://www.linkedin.com/company/teamblue/) — 32.6k followers |
| **Website** | team.blue |
| **Blog** | press.team.blue |

- **Product:** Ecosystem of 60+ digital service brands providing hosting, domains, email, e-commerce, and SaaS tools for SMBs across Europe.
- **Customers:** 3.5M+ SMBs and entrepreneurs across Europe and beyond.
- **Notable:** One of Europe's largest hosting/digital services ecosystems; employs 4,000+ experts; actively building AI layer across all brands; 9 Bologna alumni.

Indeed rating: Not available.

---

## Job Summary

**What they do:** team.blue is building the AI layer across one of Europe's largest digital-services ecosystems, powering hosting, domains, email, and SaaS for millions of SMBs.

**The role:** Senior Principal AI Solutions Engineer — the senior technical authority on AI systems end-to-end, from model research and fine-tuning through multi-agent orchestration, real-time inference, and production reliability.

**Core work:**
- Architect and evolve a multi-agent orchestration platform (Hermes/Multica) including plugin systems, tool-use pipelines, observability hooks, and channel adapters (voice, telephony, messaging)
- Design and implement voice AI pipelines (STT/TTS/VAD/SIP/RTP telephony) with sub-300ms latency targets and build RAG pipelines with retrieval quality measurement and hybrid search
- Fine-tune and evaluate LLMs (LoRA, QLoRA, DPO) for domain-specific tasks; own the AI observability stack (Langfuse tracing, cost tracking, quality regression alerting)

**Stack:** Python · PyTorch · HuggingFace Transformers · LoRA/QLoRA/DPO · vLLM · TensorRT-LLM · LangGraph/agentic frameworks · MCP · RAG · vector search · Langfuse · MLflow · Docker · Kubernetes

**Work style:** Fully remote, Dublin-based company, EU work authorization required.

---

## Score: 85%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 90% | Multi-agent orchestration platform, MCP server architecture, tool-use pipelines, voice AI agents, RAG — among the deepest agentic AI scope seen in this search |
| Tech fit (25%) | 85% | Python, PyTorch, HuggingFace, LoRA, vLLM, MCP, RAG, Langfuse — excellent stack overlap; voice/speech is a gap but secondary |
| Remote fit (25%) | 100% | Fully remote |
| Company culture fit (15%) | 55% | Large EU ecosystem (3,000+ employees, 60+ brands) — not AI-native startup, but actively investing in AI seriously across all brands |
| IC/leadership balance (10%) | 80% | Explicitly hands-on IC: "not a research-only role and not an MLOps-only role. You will do both." Technical leadership over junior engineers. |
| **Final (weighted)** | **85%** | |

---

## Strengths

- Deepest agentic AI scope seen in this scan: multi-agent orchestration, MCP, voice AI pipelines, RAG, fine-tuning all in one role
- Fully remote, Dublin-based; EU work authorization (Luca already has it)
- Strong tech stack overlap (Python, PyTorch, HuggingFace, vLLM, MCP, RAG)
- Only 12 applicants in first 24 hours — very early
- 9 Bologna alumni at the company — warm network possible

---

## Weaknesses & Risks

- Salary undisclosed — large EU hosting company may underpay for a Principal AI role
- team.blue is not an AI-native startup; large ecosystem company (3,000+) with slower culture
- Voice AI/speech (ASR/TTS/VAD/SIP) is a gap — Luca has audio ML background from Fenergo era but not deep voice pipeline ops
- Principal-level expectations (8+ years, 2+ years lead/staff) — seniority bar is high

---

## Suggestions

- Emphasize agentic orchestration work and MCP server experience (strong match)
- Highlight RAG pipeline design and LLM fine-tuning experience
- Mention audio ML background as a bridge to the voice AI pipeline requirement
- Ask about: salary range, team size, current state of Hermes/Multica platform, and roadmap for the AI layer

---

## Interview Tracker

| Stage | Date | Notes |
|---|---|---|
| Applied | | |
| Recruiter screen | | |
| Technical interview | | |
| Final round | | |
| Offer / Outcome | | |