$ cat jobs/applied-ai-engineer-m-w-d-sixt-21722a0442d4.json
Applied AI Engineer (m/w/d)
Are you passionate about building intelligent systems that solve real world challenges at scale? You will design and develop AI powered solutions that transform how SIXT operates globally, from intelligent automation to advanced predictive systems. Working at the intersection of AI, engineering and business, you will turn complex challenges into scalable products with measurable impact. Ready to shape the next generation of AI driven solutions in Pullach close to Munich? Apply now and join Team Orange as Applied AI Engineer (m/f/d)! YOUR ROLE AT SIXT You design and build scalable, production ready AI automation frameworks and agentic workflows that integrate seamlessly into SIXT's technology ecosystem You translate complex business challenges into technical solutions, selecting and implementing the most effective approaches across agentic architectures, MCP integrations, predictive models and neural networks You take ownership across the full product lifecycle, from solution design and API development to containerization and deploying scalable applications in partnership with Software Engineering teams You collaborate directly with senior stakeholders and business leaders, translating strategic priorities into scalable technical architectures and impactful data products You continuously optimize and evolve AI systems, ensuring technical excellence and scalable performance across global operations You actively shape our engineering culture by contributing to the tech stack, challenging existing approaches and sharing knowledge across teams YOUR SKILLS MATTER Experience You hold a Master's degree in a STEM field and bring hands on experience in AI Engineering, Data Science or Software Engineering within fast paced and technology driven environments AI Expertise You have a strong foundation in modern GenAI frameworks and agentic patterns such as LangChain and MCP, combined with practical experience in Deep Learning frameworks like PyTorch and classical ML libraries suc
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