Jobbörse

Chapter Lead AI Engineering (f/m/d)

Veröffentlicht am 09. Okt. 2026

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Vestigas

München (Hybrid)

EnglischLeadFließend Deutsch (C1+)

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Gehalt (Schätzung)

Grobe Schätzung: etwa 68.000 €/Jahr

Über diese Stelle

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 Chapter 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 experience in technical leadership and take responsibility for the AI engineering chapter across Scrum teams, shaping architecture, aligning technical standards, and enabling engineers to build dependable AI systems. This is a hands-on technical leadership role.

The Technical Challenge Your chapter 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 chapter navigates that trade-off, deciding where to push automation further and where human review still matters. Agentic AI systems that plan, use tools, and act on their own are an increasingly important part of this work as well.

Provide technical leadership for the AI engineering chapter, own its technical direction and strengthen shared engineering practices across Scrum teams
Own MLOps processes and infrastructure, ensuring our AI systems are reliable, scalable, and secure
Drive the design and implementation of advanced AI features, partner 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
Ensure the scalability, maintainability, and core functionality of our AI solutions – and drive the build of new ones from scratch
Translate customer needs into technical priorities and represent AI engineering in strategic product and sales discussions
Establish and evolve engineering standards, tooling, and quality practices across the chapter
Mentor fellow AI engineers through technical feedback, pairing, and knowledge sharing
Champion the use of modern AI tools such as Claude or Cursor across the chapter

Bachelor's or Master's degree in Engineering, Computer Science, or a related field; alternatively, an equivalent education
You have at least five years of AI engineering experience, including one year of technical leadership, with practical responsibility spanning the AI lifecycle and MLOps
Demonstrated ownership of technical decisions, with the ability to align engineers across teams and mentor peers
Hands-on expertise in natural language processing and image processing
Strong Python skills and experience with Azure; Terraform experience is a plus
A passion for generative AI, OCR, and building customer-focused solutions
A habit of writing clean, well-tested code with an eye on what happens after deployment
Solid understanding of AI agents, tools, and their limitations
Fluent English and German (C1 or above)
Willingness to work from our Munich office at least two days a week

Real ownership instead of micromanagement. You shape, you decide, and you see the impact of your work directly in the market.
Direct line to founders and leadership. Flat hierarchies are our everyday reality – short paths, fast decisions.
AI-First workflow. Copilot, Claude, Cursor & co. are standard tools for us. We expect and support their use.
Hybrid work with an office in the heart of Munich, just around the corner from Theresienwiese. Flexible setup with regular office presence – because we believe the best ideas happen in person.
EGYM Wellpass or BahnCard, corporate benefits, team events, annual offsites.
Fair, competitive compensation.

Chapter Lead AI Engineering (f/m/d)

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