Senior Solutions Architect – Data & AI Engineer, German-Speaking

• Develop and implement scalable AWS architectures for data platforms and GenAI/Agentic AI solutions.
• Ensure security, performance, reliability, and cost efficiency in accordance with the AWS Well-Architected Framework.
• Make and document architectural decisions, including trade-offs.
• Translate business pain points into measurable technical requirements and clear objectives.
• Continuously improve existing standards.
• Contribute to technical pre-sales, project scoping, and the preparation of Statements of Work.
• Develop generative AI and agentic AI solutions on AWS Bedrock using Strands Agents and Bedrock AgentCore.
• Develop agent architectures featuring tool use, MCP-based integrations, multi-step orchestration, and clearly defined agent-scope boundaries.
• Implement human-in-the-loop patterns, approval steps, escalation logic, and automated review loops.
• Establish evaluation and quality assurance processes for LLM and agent systems.
• Advise customers on the pragmatic and responsible use of GenAI and agentic AI.
• Act as a trusted technical advisor and support technical workshops.
• Translate complex technology into clear business value.
• Mentor junior colleagues.
• Contribute to internal standards, best practices, and training programs.

• 5+ years of experience in cloud, data, software, or ML engineering, including 2+ years owning end-to-end architectures.
• Strong hands-on expertise with AWS.
• Solid experience in data engineering and ETL architectures.
• Experience with generative AI and agentic AI projects.
• Excellent Python skills.
• Fluent English.
• Professional-level German.
• AWS certifications (nice to have).
• Experience in pre-sales or technical leadership (nice to have).
• Experience in consulting or customer-facing projects (nice to have).
• Experience with AWS Connect (nice to have).
• Solid experience with IaC, such as Terraform or an equivalent technology (nice to have).
• Experience with LLM customization, fine-tuning, and distillation (nice to have).
• Practical MLOps experience, including model deployment, monitoring, and lifecycle management (nice to have).
• Experience with Kafka/streaming (nice to have).

• Four-day workweek with a reduced 36-hour working week, allowing you to focus fully on impact.
• Attractive compensation package with a partially variable component, depending on your experience.
• Fast, transparent hiring process—typically no more than three interviews, with an offer usually made within four weeks.
• Personalized mentoring and structured onboarding from day one.
• AWS certifications fully funded by us.
• Remote-friendly setup with limited travel—no more than 20% on average per year.
• Regular team and after-work events at our locations, plus shared offsites.