AI Engineer

Are you an AI Engineer with backend experience who has gone deep on LLMs and wants to own an entire AI product area rather than pick up tickets on someone else's? A hospitality technology company whose platform runs live restaurant operations is building its first AI features, and needs one person to own all of them. 📍 Fully remote, Europe💷 €75,000 to €100,000 plus equity - Hired on a B2B basis🤝 Interview Process:3 stages:Conversation with the FounderTechnical Product Discussion with the Engineering TeamAI Assessment with an External Specialist including a technical test Tech Stack: Python · OpenAI, Claude, Gemini, Llama, Mistral · RAG, embeddings and vector search · PostgreSQL · AWS The platform is live, in production, and already carrying serious load. This is not a company bolting AI on to look modern. It is a company sitting on real operational data that AI can make genuinely more useful. Over 100 million transactions processed to dateAround 500GB of live operational data across restaurant customersSeries A closing, with revenue growing month on monthAn engineering team of eight: CTO, three backend, mobile, frontend, data and DevOps The next step is turning that platform and that data into AI features restaurant operators actually use every day. That is where you come in. You will own the AI product area end to end, as the first and only person in it. The RoleYou will work alongside the backend, data and DevOps engineers and report into the CTO, but the AI area is yours. You decide which models suit which problem, you build the systems, you set the quality bar, and you take the features into production. Nobody above you will dictate the provider, and nobody below you will build it for you. What You Will Be Doing: Building conversational retrieval over a large body of internal documentation, so users get answers that are grounded and correct rather than plausibleTurning messy customer-supplied files, PDFs, photographs, spreadsheets and whatever else arrives, into clean structured data inside the platform against a defined schemaMaking live operational data queryable in plain English by customers who do not write SQL, and being accountable for the answers being rightChoosing and combining models across providers based on what each job needs, and being able to explain the tradeoffsDesigning retrieval end to end: embeddings, chunking, vector search and the document pipeline behind itTranslating natural language into safe, correct queries against live operational dataBuilding the evaluation, guardrails and fallbacks that stop the system quietly getting things wrong in front of paying customersIntegrating all of it into the existing point of sale, dashboard and backend systems Experience We Are Looking For:Strong Python with a real backend engineering background behind itAround eighteen months or more building with LLMs properly, not occasional experiments alongside other workFeatures you have taken all the way into production, that real users depend onHands on with more than one provider, and able to argue the case for one over another. OpenAI, Claude / Anthropic, Gemini, Llama, Mistral or similarRAG, embeddings, vector search and document retrievalStructured outputs, function and tool callingExtracting structured data from PDFs, images, CSVs and spreadsheetsStrong SQL and PostgreSQLExposure to evaluating output quality, hallucination, guardrails and fallback behaviourComfortable deploying and running your own work on AWS or similarA startup or scaleup background where you owned something whole rather than a slice of it Nice To HaveText to SQL or semantic layer experienceLangGraph, LlamaIndex, LangChain or similarOCR, document parsing and multimodal modelsVector databases and retrieval infrastructure at scaleEvaluation datasets and automated regression testingFine tuning or model adaptationRestaurant, hospitality, point of sale, payments or analytics experienceElixir or Phoenix, or experience working alongside an Elixir backend team This is not the role for you if you want a large AI team around you, an established platform team to lean on, or a defined backlog handed over each sprint. It is the role for you if you have been the person building the LLM features at your current company and you now want the whole area, the model decisions, and your name on it. This is a senior role. Not a 9-5, not a 9-9-6. Judged on output. Apply for consideration