P bAbout /b bTextYess /b /ppFor thousands of years, commerce was human. Merchants knew their customers, understood their needs, and built trust through real conversations. Then came the internet, and we traded humanity for scale. Shopping became efficient but soulless: endless product grids, generic descriptions, no one to guide you. /ppbrSi candidi in fretta: consulti la descrizione completa scorrendo verso il basso per scoprire tutti i requisiti di questo ruolo.br/ppTextYess is here to restore what was lost. We build AI agents that bring back the personal, conversational shopping experience, at infinite scale. Through WhatsApp and messaging apps, we help brands sell through tailored, real-time conversations that feel natural, helpful, and human. /ppbr/ppWe work with brands like Ducati, Pittarosso, Piazza Italia, and Doppelgänger. We closed a €2.4M seed round and we're just getting started. /ppbr/pp bThe Role /b /ppYou'll be our second AI engineer, working alongside Luis (AI Lead) in a seven-person engineering team led by Valdo (CTO). The team is all internal, full-stack leaning, and ships weekly. We're remote-first with an office in Milan. /ppbr/ppTextYess runs AI agents on WhatsApp, onsite chat, and voice (with email launching next). Today, these agents are mostly reactive: they answer customer questions using a RAG pipeline over product catalogs, brand knowledge, and QA pairs. The next step is making them genuinely autonomous: agents that take multi-step actions, reason over long conversations, proactively drive revenue, and work across channels with a shared intelligence layer. /ppbr/ppThat's what you're here to build. /ppbr/ppOur agents have handled over 3 million unique customer conversations across 250+ active merchants, with 12 million+ messages sent. The data is there. The challenge now is making the intelligence match the scale. /ppbr/ppbWhat you'll work on: /b /pp→ Own and improve the RAG pipeline: chunking, re-ranking, context assembly, embeddings /pp→ Build evaluation frameworks to measure agent performance systematically, not anecdotally /pp→ Design and ship the multi-agent architecture for cross-channel orchestration /pp→ Fine-tune models on our proprietary dataset: millions of real merchant-customer conversations, orders, and product catalogs /pp→ Define the AI capabilities that are uniquely ours /ppbr/ppWe're an AI-native team: coding agents, agentic workflows, and automated review are part of how we work every day. We expect you to bring that same fluency. /ppbr/ppb Who You Are /b /ppYou've shipped AI systems that real users depend on. You know that evals matter more than vibes, that RAG breaks in production in ways it never does in demos, and that the gap between a good agent and a great one is mostly invisible until you measure it. You have opinions, you push back when something is wrong, and you move fast. /ppbr/ppbMust-haves: /b /pp→ Production experience with LLMs, agents, and multi-agent systems /pp→ Strong RAG experience: you know when it works, when it doesn't, and why /pp→ Python skills strong enough to build from scratch /pp→ Fluent with the modern LLM stack: OpenAI, Anthropic, open-source models /ppbr/ppbBonus: /b /pp→ Rigorous about evaluation: you don't ship AI without measuring it /pp→ Experience fine-tuning LLMs for specific domains /pp→ Cloud infrastructure experience for AI/ML at scale /pp→ Background in eCommerce or conversational AI /pp→ Vector databases and semantic search at scale /ppbr/ppb Compensation /b /ppStarting from €60,000 RAL. We're a seed-stage startup, we pay competitively and we're flexible for the right person. If you're senior and you know it, talk to us. /ppbr/ppStock options included. If TextYess becomes something big, you share in it. /ppbr/ppb Hiring Process /b /pp1. 30-min Intro Call /pp2. 30-min Tech Team Meet /pp3. Take-Home Assignment /pp4. 60-min Technical Deep Dive /pp5. 60-min Founder (CEO) Conversation /ppbr/ppb Interested? xdwybme Send an email to. We'd love to chat. /b /p