Team Lead AI Engineering (f/m/d)

6 requirements, read out of the advert rather than guessed from the job title:

• AI engineering
• MLOps
• natural language processing
• image processing
• Python
• Azure

Also mentioned, not required: Terraform, English (C1), German (C1). Worth having, but their absence is not what gets a CV filtered out.

We're digitizing the construction industry – are you in? At VESTIGAS, you build the digital backbone of the construction supply chain. We turn purchase orders, delivery notes, and invoices into a digital, legally compliant platform used in everyday operations by construction companies and suppliers. You’ll work on a product with real market traction in the DACH mid-market, ship iteratively, and take ownership of solutions that must work in the field—not just in theory.

Your Role As Team Lead – AI Engineering, you'll own the AI infrastructure and capabilities that power our supply chain platform end to end – from pipeline design to production deployment. You bring prior leadership experience and are ready to lead a team of AI engineers: setting technical direction, growing your team's capabilities, and making sure the team consistently delivers reliable, scalable AI systems. The Technical Challenge Your team will tackle problems like extracting structured data reliably from many different documents, building uncertainty estimation so the system knows when to flag a document for human review instead of silently guessing, and automatically reconciling purchase orders, delivery notes, and invoices against each other – all within legal and compliance requirements that leave no room for "close enough." This is a domain where clean benchmark metrics mean far less than robustness against real documents nobody has seen before – and you'll set the technical direction for how the team navigates that trade-off, deciding where to push automation further and where human review still matters.

Your Mission Lead and long-term grow a team of AI engineers, providing both strategical technical direction and people leadership

Own MLOps processes and infrastructure, ensuring our AI systems are reliable, scalable, and secure

Drive the design and implementation of advanced AI features, partnering closely with engineering and product leadership to deploy machine learning models and data pipelines

Set the bar for accuracy, efficiency, and uncertainty estimation of our AI features through rigorous testing practices