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# Senior AWS Solutions Architect

- **Company:** Siemens Energy
- **Location:** Erlangen, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Cloud Engineering, Data Architecture, Information Engineering, Data Infrastructure, Identity and Access Management, Python (Programming Language), Machine Learning, Cloud Services, Technical Data Management Systems, Enterprise Data Management, Generative AI, Event Driven Architecture, Build Management, Machine Learning Operations, Virtual Agents, Serverless Computing, Microservices
- **Published:** July 30, 2026
- **Apply:** https://www.myability.jobs/de/node/171106/apply-external

## About the Role

* Several years of professional experience in defining architecture standards, reusable components and platform governance on AWS or similar (preferably in the context of Machine Learning or GenAI)
 * Advanced Python skills for cloud services, automation, and AI / ML workloads
 * Experience designing serverless, microservice, and event-driven architectures
 * Experience implementing MLOps / GenAIOps pipelines and model lifecycle management
 * Solid understanding of modern data architectures and integration with enterprise data platforms

## Description

We are looking for a Senior AWS Solutions Architect (f/m/d) to design and govern the cloud architecture that enables our enterprise AI and data platform. The role focuses on establishing scalable AWS foundations for AI, machine learning, and generative AI applications, while ensuring alignment with the organization's broader data platform, governance, and engineering standards.

You will work closely with data engineers, technical data architects, AI engineers, and external partners to ensure that our cloud environment reliably supports GenAI, Agentic AI, and Retrieval-Augmented Generation (RAG) use cases. A key part of the role is defining reusable architecture patterns, platform components, and operational frameworks that allow teams to build and deploy AI solutions efficiently and securely.

How You'll Make an Impact

 * Define secure and scalable AWS environments, including account structure, IAM models, networking, and guardrails
 * Ensure cloud solutions meet enterprise standards for security, reliability, performance, and cost efficiency
 * Define and maintain the cloud architecture for AI / ML and GenAI workloads on cloud infrastructure (preferred AWS).
 * Design and implement scalable platform components and reusable reference architectures for AI and data teams.
 * Establish MLOps / GenAIOps frameworks for model deployment, monitoring, and lifecycle management
 * Collaborate with data engineering and architecture teams to ensure the platform supports RAG pipelines, agentic systems, and advanced AI applications


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