About the role
About
Storm Reply specializes in the development and implementation of innovative, AWS-based solutions and services within the Reply Group. Expertise in Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) forms the foundation for holistic support throughout the entire cloud transformation journey. Measurable business value is created through the use of AWS. As an "AWS Premier Consulting Partner," Storm Reply supports leading European and global companies in the introduction and operation of business-critical cloud systems and applications. Through the targeted use of AI and generative AI from the AWS portfolio, processes are automated and innovative strength is sustainably strengthened. This creates a scalable, cloud-based foundation for the continuous transformation of business models.
AWS AI & Data Engineer (m/f/d)
Munich
Responsibilities
- Develop end-to-end AI solutions on AWS – from initial prototypes to scalable, production-ready applications with MLOps and LLMOps best practices
- Build scalable data and AI infrastructures as well as AI agents based on AWS services such as Amazon Bedrock, Amazon Bedrock Agent Core, AWS Glue, AWS Lambda, or Amazon SageMaker
- Utilize Generative AI and Machine Learning to realize intelligent systems, AI agents, and RAG architectures with vector databases
- Conceptualize innovative solutions together with Data Engineers, Developers, and Architects, support customers from idea to go-live, and share your knowledge within the team
- Automate deployments, monitoring, and infrastructure with Infrastructure as Code (CDK, Terraform, CloudFormation) and CI/CD tools like CodePipeline and CodeBuild
Requirements
- Successfully completed studies in Computer Science, Mathematics, Physics, or a comparable qualification
- Initial professional experience in the cloud – ideally with AWS – is a plus (e.g., Amazon SageMaker, Amazon Bedrock, AWS Lambda)
- Experience in programming with Python, ideally complemented by practical knowledge of frameworks like LangChain, LangGraph, or Strand Agents
- Enjoy actively shaping new technologies and trends and are enthusiastic about Generative AI, MLOps/LLMOps approaches, and modern cloud architectures
- Enjoy working with customers, understanding their requirements, and developing solutions that create real added value
- Fluent in spoken and written German and English
What We Offer
- Flat hierarchies, short decision-making processes, and genuine co-creation – actively influence projects and processes
- Always up-to-date: external and internal training opportunities as well as certifications
- Modern work environment in an innovative and international team with regular team events
- Buddy program for a smooth start and quick networking within the team
Requirements
- Successfully completed studies in Computer Science, Mathematics, Physics, or a comparable qualification.
- First professional experience in the cloud – ideally with AWS – (e.g., Amazon SageMaker, Amazon Bedrock, AWS Lambda).
- Experience in programming with Python, ideally supplemented by practical knowledge with frameworks like LangChain, LangGraph, or Strand Agents.
- Enjoy actively shaping new technologies and trends and are enthusiastic about Generative AI, MLOps/LLMOps approaches, and modern cloud architectures.
- Enjoy working with customers, understanding their requirements, and developing solutions that create real added value.
- Fluent in spoken and written German and English.
Responsibilities
- Develop end-to-end AI solutions on AWS, from prototypes to production-ready applications with MLOps and LLMOps best practices.
- Build scalable data and AI infrastructures as well as AI agents based on AWS services like Amazon Bedrock, Amazon Bedrock Agent Core, AWS Glue, AWS Lambda, or Amazon SageMaker.
- Utilize Generative AI and Machine Learning to realize intelligent systems, AI agents, and RAG architectures with vector databases.
- Conceptualize innovative solutions with Data Engineers, Developers, and Architects, guide customers from idea to go-live, and share knowledge within the team.
- Automate deployments, monitoring, and infrastructure with Infrastructure-as-Code (CDK, Terraform, CloudFormation) and CI/CD tools like CodePipeline and CodeBuild.
Benefits
Skills
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