Agentic AI engineer for BMW innovation Solutions

What awaits you! Join our team to industrialize sophisticated cutting-edge AI for our next generation of Innovations at BMW.The role involves designing, developing, and refining Agentic AI based workflows that will form the core of our innovative AI-driven products and services.The ideal candidate will possess deep expertise in generative AI practices, with the ability to build and scale Agentic AI applications end-to-end from architecture and orchestration to cloud deployment and production operation.Own the design and delivery of GenAI-powered applications, translating business problems into robust, agent-driven solutions with measurable outcomes.Deploy, scale, and operate AI applications on cloud platforms (AWS/Azure), leveraging managed AI/ML services, containerization, and cloud-native architecture patterns.Embed AI agents into automotive software pipelines to enable adaptive behaviours, such as real-time anomaly detection during unit testing or automated regression analysis in system validation.Develop and maintain AI-based tools for model-based development, system diagnostics, code generation, and continuous integration.Drive processes in a structured and organized manner from requirement gathering through to deployment ensuring predictability and traceability across the AI application lifecycle.Stay abreast of emerging agentic AI trends and cloud-native AI services, quickly upskilling and proposing integrations that advance our software capabilities.In your daily work, you will find yourself in an international and interdisciplinary environment with an agile mindset.Our campus offers the cloud infrastructure you need to work productively with large amounts of data and focus on the software for the automobile of the future.What should you bring along! 4-7 years of experience in AI/ML research and development, with a strong focus on Generative AI application creationProven, hands-on experience building and deploying Agentic AI frameworks and multi-agent systems in production environmentsStrong hands-on experience deploying and operating AI/ML applications on AWS and/or Azure including compute (EC2/Azure VMs), managed AI services (SageMaker/Azure ML, Bedrock/Azure OpenAI), containerization (Docker/Kubernetes), storage, and networking basicsProven experience with generative model architectures and techniques, as well as fine-tuning methods to improve model performanceFamiliar with implementing RAG (Retrieval-Augmented Generation) architecture for sophisticated AI applicationsExperience setting up CI/CD pipelines for AI application deployment (Jenkins, GitLab CI, or cloud-native pipelines such as AWS CodePipeline/Azure DevOps)Demonstrated ability to quickly grasp new tools, frameworks, and emerging cloud/AI concepts, and apply them pragmaticallyStrong process orientation able to structure and drive complex AI initiatives in an organized, transparent, and repeatable wayKnowledge of MLOps practices to ensure the robustness and reliability of AI systems in productionStrong Python programming skills and experience with modern AI frameworks (PyTorch, TensorFlow, LangChain/LangGraph, or similar agentic frameworks)Excellent communication and collaboration skills, with the ability to lead and mentor junior team membersBusiness fluent knowledge of English (written and spoken) .