We'rethe AI-first CRM that turns conversations into revenue. On-site, WhatsApp, email, voice: our AI Agents sell, support, and retain customers for the best B2C brands out there, autonomously.

We believe the future of commerce is warmer, more human than ever - just at a scale no human team could pull off alone.

We've raised €3M+ and work with brands like Ducati, Pittarosso, MC2 Saint Barth, and Doppelgänger. We're a lean, fast, Italian-born scale-up now expanding our story internationally and this role is a big part of writing it.

The role

Join our AI team to build the agentic runtime for proactive agents: context building, tool/retrieval orchestration, scoring, and guardrails. You’ll own production components from day one and work directly on the “signal vs. noise” call.

What you'll actually be doing

- Grounding. The agent sometimes says a product is unavailable when it's in stock. Fixing that is a retrieval problem, a prompt problem, and an eval problem at the same time.
- Exact match vs. semantic. Semantic search is good at "warm jacket for winter" and bad at a SKU, a size, or a specific variant. We need both, in one ranking.
- Multilingual quality. Our customers write in Italian, English, and more. An agent that answers in the wrong language is worse than one that says nothing.
- Latency and cost. A customer is waiting on their phone. You'll profile requests, test prompt and model changes, and ship improvements you can point at on a graph.
- Evals that catch problems before customers do. Every conversation has a Langfuse trace, and we have a golden-dataset harness. Making it actually predict production quality is open work.
- Deciding what's worth saying. Ranking, scoring, and suppressing proactive insights so the agent interrupts a customer only when it has earned it.

What you bring





- 2+ years shipping software professionally , including at least one LLM feature real users touched — a chatbot, a RAG system, an agent. Not a weekend project.
- You know how RAG actually behaves : embeddings, vector search, chunking, reranking, and where each one breaks.
- You can read traces. Given a bad answer in production, you can find why: retrieval missed, the prompt was wrong, the model picked the wrong tool. Langfuse, LangSmith, Braintrust, Arize, Humanloop — any of them.
- Strong Python and backend fundamentals , and the instinct to measure latency, cost and quality instead of guessing.
- Nice to have: search infra (Elastic, Algolia, Qdrant, Weaviate), fine-tuning, graph search, you know how e-commerce operate.

Why TextYess

- Real ownership, from day one. No layers, no waiting your turn: you'll own outcomes, not just tasks.
- Lean team, big impact. You'll work shoulder-to-shoulder with top-notch international talent, ready to disrupt and leave a mark.
- Build, don't maintain. We're early enough that most of what you touch doesn't have a playbook yet, you get to write it.
- Grow as fast as you push. Roles and responsibilities scale with what you prove you can do, not with tenure.
- A team that actually likes each other. We're a dynamic, close-knit crew that moves fast, laughs a lot, and has each other's backs.

Our hiring process

We keep it real and reasonably fast:

- Screening call , let's just talk. Communication, fit, the basics.
- Interview + live case study , Let’s deepdive into technicalities of the role.
- Founder & Team conversations , here you meet the people you'd actually work with.
- Debrief, reference check, and decision . We move quickly once we're there.

TextYess is an equal opportunity employer. We welcome applicants of all backgrounds and experiences.

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📌 Artificial Intelligence Engineer (Italia)
🏢 TextYess
📍 Italia