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Senior AI Engineer (f/m/d)

Vestigas · München (Hybrid)

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Dari iklan pemberi kerja · Vestigas · diterbitkan 9 Oktober 2026

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

You'll help build the AI infrastructure and capabilities that power our supply chain platform, working across the full lifecycle – from pipeline design to production deployment. With 5+ years of experience under your belt, you're ready for the next step in your career. Maybe you've already mentored or technically guided colleagues, and you're looking to grow steadily into a Team Lead role as you take on more ownership and, over time, people responsibility.

The Technical ChallengeYou'll work on 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 you've never seen before, and where every accuracy gain has a direct, visible impact on our customers' daily operations.

Your Mission

  • Lead MLOps processes and maintain infrastructure to keep our AI systems reliable, scalable, and secure
  • Design and implement advanced AI features, working closely with engineering and product teams to deploy machine learning models and data pipelines
  • Improve the accuracy, efficiency, and uncertainty estimation of existing AI features through rigorous testing
  • Contribute to the scalability, maintainability, and core functionality of our AI solutions – and help build new ones from scratch
  • Align your technical work with customer needs and support product and sales discussions
  • Help establish engineering standards, tooling, and quality practices
  • Mentor and technically guide colleagues as you build the track record to grow into a leadership role
  • Use modern AI tools such as Claude or Cursor as part of your daily workflow

Your Profile

  • Bachelor's or Master's degree in Engineering, Computer Science, or a related field; alternatively, an equivalent education
  • 5+ years of experience in AI engineering, including end-to-end lifecycle management and MLOps
  • 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
  • Ideally, some experience mentoring or technically guiding others – and the ambition to grow into a Chapter Lead role
  • Fluent English and German (C1 or above)
  • Willingness to work from our Munich office at least two days a week

Your Benefits

  • 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.

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Keahlian yang disebutkan

MLOpsMachine LearningEnd-to-end ML lifecyclePythonMicrosoft AzureTerraformGenerative AIOCRAI AgentsData PipelinesProduction DeploymentUncertainty Estimation

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