Summary
✨ AI‑Generated
A technical leadership role responsible for guiding AI engineering projects, managing a development team, and building production-ready solutions using modern AI methods.
Highlights
Leadership position combining hands-on AI engineering with team management and modern machine learning practices.
Description
This job is on behalf of Juucy.io's client.
Requirements▪ Bachelor’s or Master’s degree in Engineering, Computer Science, or a related field; alternatively, an equivalent education
▪ At least 5 years of experience in AI engineering and 1 + year in a leading position, including end-to-end lifecycle management and MLOps
▪ Proven experience leading or managing a technical team, with strong people-leadership skills
▪ Hands-on expertise in natural language processing
▪ Hands-on expertise in image processing
▪ Strong Python skills
▪ Experience with Azure
▪ Terraform experience is a plus
▪ Experience with generative AI and OCR
▪ Solid understanding of AI agents, tools, and their limitations
▪ A habit of writing clean, well-tested code with an eye on what happens after deployment
▪ Fluent English and German (C1 or above)
▪ Willingness to work from our Munich office at least two days a week
Tasks & ResponsibilitiesYou'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.
▪ Lead and long-term grow a team of AI engineers, providing both strategical technical direction and people leadership
▪ Own the AI infrastructure and capabilities that power our supply chain platform end to end – from pipeline design to production deployment
▪ 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
▪ Translate customer needs into technical priorities and represent AI engineering in strategic product and sales discussions
▪ 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
▪ Establish and evolve engineering standards, tooling, and quality practices across the team
▪ Coach and develop your team members, supporting their technical and professional growth
▪ Champion the use of modern AI tools such as Claude or Cursor across the team
Core Benefits▪ High level of autonomy with a direct reporting line to the founders and very flat hierarchies.
▪ A leadership role with creative freedom: you’ll build out the AI team, set the technical roadmap, and be responsible for the entire MLOps infrastructure.
▪ Work on real-world NLP, OCR, and uncertainty challenges that power the digital backbone of the construction supply chain for over 1,000 companies.
▪ An AI-first environment with modern tools like Copilot, Claude, and Cursor as standard tools.
▪ Attractive overall package: €80,000–110,000 fixed salary, 26–30 vacation days, EGYM Wellpass or BahnCard, corporate benefits, team events & offsites.
▪ Hybrid setup at our downtown Munich office plus flexible work-from-home days, with no travel required.
▪ Fast-growing scale-up with proven market success and a mission to make the construction industry more sustainable and efficient.
Required Experienceminimum 5 years experience
Employment TypeFull-time
Hiring Process1.
Application via juucy Talent Partner
2.
Initial interview
3.
Technical interview
4.
Final interview