Senior AI Engineer — Enterprise SaaS (FMCG Retail)

About the job

Remote · Germany · Full-time

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.

The opportunity

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 forecasting, classification)
• You understand that AI moats come from data flywheels, not model access — and you know how to build them
• Experience deploying and rolling out SaaS solutions into enterprise‑size clients — you've dealt with phased onboarding, UAT with multiple stakeholder groups, and the messy reality of making software work across large organizations

Core technical stack (must be reflected in CV and experience)

• Frontend: Next.js (React-based frameworks, SSR/ISR concepts)
• Backend: NestJS (Node.js framework, REST/GraphQL APIs)
• Python backend (at least one): Django or FastAPI — important for integration with our existing platform
• Databases: PostgreSQL + vector databases for AI workloads
• LLM APIs: OpenAI / Anthropic integration and orchestration

Additional technical expectations

• Strong proficiency with Git (branching strategies, pull requests, code reviews, conflict resolution)
• Experience working in containerized environments (Docker)
• Familiarity with CI/CD pipelines and automated deployments
• Experience with API design, versioning, and integration patterns (ERP, POS, CRM)
• Knowledge of authentication/authorization systems (JWT, OAuth, RBAC)
• Experience with event‑driven architecture (webhooks, pub/sub, message queues) for real‑time data flows
• Multi‑tenant enterprise systems with proper data isolation, audit logging, and GDPR compliance
• Experience with computer vision pipelines (object detection, image classification) is a strong plus
• Testing, monitoring, and observability — you ship with confidence, not crossed fingers
• Ability to write clean, maintainable, and well‑documented code
• Comfortable working alongside another engineering team and defining clean API boundaries between systems

Nice to have

• Experience with distributed systems or microservices architecture
• Familiarity with message brokers (e.g., Redis, queues)
• Exposure to cloud environments (GCP, AWS, or similar)
• Experience working on SaaS products at scale
• Retail/FMCG domain knowledge
• Experience with marketplace/transactional platforms
• Mobile‑responsive or PWA experience for in‑store use cases
• Prior experience at a company that scaled past Series B

Languages:

Fluent German and English required. French is a plus.

Why this role

• First technical hire for the enterprise product — with full ownership of architecture and the opportunity to build and lead the Enterprise engineering team over time
• You won't be alone — there's already senior engineers running the marketplace platform. You'll define the enterprise side and the bridge between both.
• Direct access to founders — no PM layer, no ticket queue
• Competitive salary
• Real market — €600B+ European retail, not a speculative bet
• The company is early‑stage, fast‑moving, and hands‑on — we are building with real users from day one

AI capabilities that matter for this role

• Recommendation engine + data flywheel
• Computer vision for shelf compliance
• Predictive analytics / forecasting
• AI agent workflows
• Classical ML + LLMs combined

Process

• Intro call (30 min) — mutual fit
• Technical deep-dive (60 min) — architecture, past work, real scenarios
• Offer

Job Type: Full-time

Pay: From 5.000,00€ per month

Work Location: Remote

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