Senior AI Engineer — Enterprise SaaS (FMCG Retail)

About the job

Remote · Germany · Full-time • *The opportunity**

We're building an enterprise platform that sits at the center of how retailers and FMCG brands work together — managing supplier activations across store networks, coordinating headquarters with field operations, and giving brands structured access to retail spaces and campaigns. Think of it as the operating system for retail trade execution.

Two integrated products: an enterprise SaaS for retailers and brands, and a marketplace connecting brands with retail networks. AI is the foundation, not a bolt-on. The marketplace is already built and managed by its own team. Now we're looking for a senior AI engineer to build the enterprise solution from the ground up — a separate but interconnected product targeting large retail chains, franchise networks, and FMCG brands looking to manage their key account relationships and trade activations through a single platform.

• *Enterprise scale means enterprise complexity.** This solution will be deployed into real retail groups — think one HQ coordinating 600+ stores, each with their own shops, suppliers, and activation calendars. But also into FMCG brands, negotiating retail activations with a large amount of stakeholders. You need to know how to architect, deploy, and roll out software into these environments: phased onboarding, user acceptance testing with multiple stakeholder groups, role-based access across HQ, store managers, and external suppliers, and the ability to handle the operational reality of enterprise clients — not just build features, but make them work in the field.

We are already in discussions with several enterprise retail groups in Switzerland and building the platform alongside early design partners. The founding team brings 15+ years of hands-on experience in FMCG distribution and retail key account management — with direct access to decision-makers at major retail chains. • *What you'll build** • *For Retailers & Franchise Networks:** • **Store network management** — stores manage booked promotional spaces in-store, with transparent activity tracking and alignment between headquarters (and its different departments), store operations and suppliers • **Headquarters dashboard** — structured tracking of supplier agreements, monitoring of sales, promotion and marketing activities, verification of in-store execution, and consolidated performance visibility across the entire network • **Supplier portal** — digital access to promotional and trend spaces, structured booking channel for activations, centralized communication with headquarters and stores, controlled and transparent supplier interactions • **Bonus and penalty mechanisms** to improve supplier agreement compliance • *For FMCG Brands:** • **Sales & trade marketing tools** — planning and coordination of retail promotions and activations, monitoring execution of campaigns at key accounts and stores, access to sell-out data, channel profitability and campaign performance, customer feedback and insights directly from the retail front • **Brand headquarters** — centralized management of retail activations and campaigns, annual planning and negotiation management with key accounts, structured tracking of agreements, budgets and marketing investments, consolidated visibility of performance across all retail partners • **Retail marketplace & network access** — direct access to the smartNsales marketplace for booking retail spaces, booking of sales placements, promotions and marketing campaigns, centralized communication with retail partners and store networks • *AI & intelligence layer:** • **Predictive analytics** — campaign ROI forecasting, sell-out predictions, and demand signals using time-series ML • **Computer vision pipeline** for shelf compliance and retail execution verification — brands pay for space, the platform proves it was delivered • **AI agent workflows** automating coordination between HQ, stores, and suppliers — campaign scheduling, compliance alerts, automated reporting, negotiation support • **Recommendation engine** that matches brands with optimal retail spaces based on historical performance and network intelligence • **Integration layer** connecting to retailer ERP/POS systems, inventory management, and CRM platforms • **Connectors and shared data layer** with our existing marketplace platform • *Minimum requirements** • Proven professional experience in software development — portfolio, Git repositories, or demonstrable production work required • 5+ years of experience in full-stack development • Strong understanding of modern web application architecture and scalable SaaS systems • Deep experience with LLMs in production (RAG, agents, orchestration) AND classical ML (recommendation systems, time-series forecasti