About the Role
We are seeking an experienced Senior Microsoft Azure AI Engineer to join our team. As a key member of our organization, you will play a crucial role in designing and implementing AI/ML solutions on Azure.
The ideal candidate will have a strong background in data analytics, software development, and cloud computing. They will be responsible for providing technical leadership to teams, developing high-level solution designs, and working closely with clients to translate their business needs into innovative AI solutions.
Key Responsibilities:
* Lead AI Solution Architecture: Develop end-to-end architectures for AI/ML solutions on Azure, from concept to deployment.
* Client Engagement: Work closely with clients to understand their business challenges and identify opportunities where AI/ML can drive value.
* Technical Leadership: Provide hands-on technical leadership to delivery teams, guiding them in implementing best practices for data preparation, model development, and cloud deployment.
* MLOps & Best Practices: Establish and enforce MLOps best practices, including reproducible workflows, CI/CD for ML models, automated testing, and monitoring of model performance in production.
* Innovation & Generative AI: Stay up-to-date with the latest AI trends and Azure services, evaluating new technologies and incorporating generative AI capabilities where relevant.
Requirements:
* Proven Experience: 7+ years of experience in data analytics and software development, with at least 4–5 years in designing and implementing ML/AI solutions at scale.
* Language Skills: Fluency in German and English.
* Azure Expertise: Deep knowledge of Azure data and AI services, including Azure Machine Learning, Azure Databricks, Azure Data Lake/Synapse, Azure Cognitive Services, and Azure OpenAI.
* Architectural Skills: Strong skills in system design and integration, comfortable defining solution architectures that encompass data ingestion, feature engineering, model training, deployment, and monitoring.
* MLOps & Software Engineering: Solid understanding of MLOps principles and experience implementing ML lifecycle management on Azure or similar platforms.
* Leadership & Communication: Excellent leadership and interpersonal skills, able to interface with client stakeholders to explain complex AI concepts in business terms.
* AI Knowledge: Broad knowledge of machine learning and AI techniques, familiarity with deep learning and NLP, and exposure to generative AI and LLMs.
What We Offer:
* Opportunity to work with cutting-edge technology: You will have the chance to work with the latest AI trends and Azure services.
* Collaborative team environment: Our team is collaborative and remote-friendly, valuing continuous learning and delivering impact through modern cloud-native data solutions.