Description

In this role, you will take technical ownership of AWS cloud-based data, machine learning, and artificial intelligence solutions, shaping the Data & AI practice while guiding customers and mentoring junior colleagues. Your day-to-day responsibilities will include designing architectures, implementing data pipelines, and ensuring the reliability of production environments.

Requirements

• •4+ years of experience in cloud, data, or ML engineering
• •Strong hands-on expertise with AWS
• •Solid experience in data engineering and ETL architectures
• •Practical MLOps experience (model deployment, monitoring, lifecycle)
• •Very good Python skills
• •Proven experience with IaC (Terraform or comparable)
• •Fluent in German and English
• •Consulting or customer-facing project experience
• •AWS certifications
• •Experience with Generative AI projects
• •Experience in pre-sales or technical leadership roles

Tasks

• •Design scalable AWS architectures for data platforms and ML workloads
• •Lead implementation and operation of data pipelines and MLOps setups
• •Ensure security, performance, and reliability in production environments
• •Build and operate end-to-end ML workflows
• •Deploy and maintain ML models using AWS SageMaker
• •Implement Generative AI use cases with AWS Bedrock
• •Guide customers on pragmatic and responsible GenAI usage
• •Act as a trusted technical advisor for customers
• •Support pre-sales activities and technical workshops
• •Translate complex technical concepts into clear business value
• •Mentor junior colleagues
• •Contribute to internal standards, best practices, and training

Tools & Technologies

Benefits