Forward Deployed Engineer - Integrations & Customer Success; f​/m​/d

We maximize product availability with minimal cashflow investment in 1/10 of the time. We solve a real problem for SMEs. With AI.

VOIDS is the AI brain for mid-size Shopify brands inventory. We forecast demand at the product level, catch stockouts and inefficiencies before they happen, and give e-commerce teams exactly the right action — or execute it automatically with a single click.

The result: 98% inventory efficiency, 20x ROI, and six-figure cash unlocked. Within weeks.

We launched in June 2023. Since then: 300% growth, 1B+ data points processed, €2M ARR, and 50+ brands live — including Hyrox, 6pm, Creamyfabrics, and Nature Heart. Now, we're targeting €10M ARR by 2028.

Today we own demand forecasting and stock management. Our vision for tomorrow: AI handles procurement end-to-end — fully autonomous.

This is where you come in. We're a small, fast team and every hire shapes the trajectory of the company. You'll shape how we ingest, process, and activate 1B+ data points, and help us build the data foundation for a fully AI-driven procurement future. Work directly with Jannik and Tobias, who live and breathe e-commerce and AI.

High autonomy. Real data scale. Work that actually ships.

We're just getting started — want to build it with us?

You’ll own the reliability and growth of our data infrastructure end-to-end. This isn't a ticket-execution role — you'll identify problems, design solutions, and ship them yourself.

• Expand our data connector ecosystem far beyond Shopify and Amazon, paving the way for complete AI-driven custom integrations.
• Evaluate, implement, and maintain new data sources in a way that works with existing flows — system stability and customization tolerance are non-negotiable.
• Work closely with customers to understand their data sources, requirements, and edge cases — you are the first technical contact when it comes to what data goes into our system.
• Communicate fluently in German and English — with customers during onboarding and pilot projects, and async with the internal team.
• Act as a bridge between customer needs and technical implementation, translating real-world data messiness into clean, reliable pipelines.
• Understand the e-commerce space intuitively - Suggest solutions to customers and implemented them before the customers even asks for it.
• Take ownership of our Bronze → Silver → Gold medallion architecture: the logic between layers needs to be airtight, well-documented, and consistent.
• Scale the piplines to new heights:
  More data, faster pipelines, less costs. You need to find abstraction layer that allow to scale across multiple customer with very unique requirements.
• Improve Developer
  
  Experience:
  
  Enable fast iterations cycles and smooth developer experience when working with existing systems or building new things on top.

• Fully embrace AI tooling — not just as a productivity booster, but as a core part of how you work: delegate end-to-end workflows (testing, development, staging, production) to AI agents where possible.
• Build and maintain AI-driven pipelines that can handle deep customisation without system failures — the architecture must be robust enough that AI-generated changes don't break production.
• Push the limits of what's achievable by combining your engineering judgment with AI automation. 10x yourself every year.

• Own the full development lifecycle: testing → development → staging → production, with automated checks at every layer.
• Set up and maintain robust testing environments and Data Ops/MLOps workflows to enable rapid iteration.
• Proactively identify bottlenecks, inconsistencies, and schema drift — and fix them before they reach downstream consumers.