Senior AI Engineer in München

About the role

We are looking for an experienced Senior AI Engineer to build and improve production grade AI systems within a complex digital supply chain environment. You will work across the full AI lifecycle, from pipeline design and model development to MLOps, infrastructure, testing, and production deployment. The role focuses heavily on real world document intelligence, including NLP, OCR, image processing, generative AI, AI agents, and uncertainty estimation.

You will tackle challenges such as reliably extracting structured information from diverse documents, determining when AI outputs require human review, and automatically reconciling related business documents under strict legal and compliance requirements. This is a senior hands-on engineering position with a clear opportunity to develop toward a Team Lead role. You will gradually take greater technical ownership, mentor colleagues, and help shape engineering standards and AI strategy.

Responsibilities

• Work across the complete AI lifecycle, from architecture and pipeline design through development, testing, deployment, and production monitoring.
• Lead and continuously improve MLOps processes and infrastructure to ensure AI systems remain reliable, scalable, secure, and maintainable.
• Design and implement advanced AI capabilities involving NLP, OCR, image processing, generative AI, and AI agents.
• Build solutions that reliably extract structured information from a wide range of real-world documents.
• Develop uncertainty estimation mechanisms that enable AI systems to recognise when a document should be escalated for human review rather than making an unreliable prediction.
• Build and improve systems that automatically reconcile related business documents and identify inconsistencies between them.
• Develop, deploy, and maintain machine-learning models, AI services, and data pipelines in close collaboration with engineering and product teams.
• Improve the accuracy, eiciency, robustness, and uncertainty estimation of existing AI capabilities through rigorous testing.
• Contribute to the scalability, maintainability, and core architecture of existing AI solutions while helping build new capabilities from scratch.
• Align technical priorities with customer requirements and contribute technical expertise to product and commercial discussions.
• Help establish and evolve engineering standards, tooling, testing methodologies, and quality practices.
• Mentor and technically guide colleagues while developing toward greater technical and leadership responsibility.
• Use modern AI-assisted engineering tools as part of the daily development workflow.
• Write clean, well-tested, production-ready Python code with strong consideration for post-deployment performance and reliability.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent relevant education and experience.
• At least 5 years of professional experience in AI engineering.
• Strong experience across the end-to-end AI/ML lifecycle, including development, deployment, monitoring, and MLOps.
• Hands-on expertise in natural language processing (NLP).
• Hands-on experience with image processing and computer vision-related applications.
• Experience with OCR and document-processing systems.
• Strong interest and practical experience in generative AI.
• Solid understanding of AI agents, tool use, and the practical limitations of agentic systems.
• Strong Python development skills.
• Practical experience working with Microsoft Azure.
• Strong knowledge of MLOps processes and infrastructure management.
• Experience with Infrastructure as Code; Terraform knowledge is an advantage.
• Ability to write clean, maintainable, well-tested, production-grade code.
• Strong understanding of what happens after model deployment, including reliability, monitoring, scalability, and ongoing performance.
• Familiarity with modern AI-assisted development tools.
• Interest in progressing toward a Team Lead or broader technical leadership position.
• Previous experience mentoring or technically guiding other engineers is an advantage.
• Fluent German and English at C1 level or above.
• Willingness to work from the Munich oice at least two days per week.
• Proactive and hands-on approach with strong communication and collaboration skills.
• Solution-oriented mindset with the ability to anticipate technical challenges and take ownership of problems.

Benefits

• Significant ownership and the opportunity to directly influence the development of production AI systems.
• Opportunity to solve complex, real-world AI challenges involving NLP, OCR, document intelligence, uncertainty estimation, and MLOps.
• Work on AI systems where improvements in accuracy and reliability have a direct impact on customers’ daily operations.
• Modern AI-first engineering environment with access to advanced AI-assisted development tools.
• Cloud-based infrastructure using technologies including Azure and Infrastructure as Code.
• Opportunity to build new AI capabilities and infrastructure from scratch as well as improve established systems.
• Clear development path toward a Team Lead position with increasing technical ownership and mentoring responsibilities.
• Flat organisational structure with close collaboration across engineering, product, and senior leadership.
• Hybrid working model with a central Munich oice and dedicated work from home days.
• No regular business travel required.
• Flexible annual leave options and additional mobility, fitness, and corporate benefits.
• Strong focus on autonomy, professional development, and sustainable work-life balance.

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