About the job

Location: Munich or Frankfurt, Germany

Experience Level: 5–12 years

Language Requirement: Fluent German and English

Role Overview

We are looking for an experienced GenAI Solutions Architect with deep machine learning and artificial intelligence expertise to design and implement production-ready Model-as-a-Service, generative AI and cloud architectures.

This role bridges complex business requirements with deployable technical solutions. You will work closely with enterprise customers, AI leaders and CTO-level stakeholders to define AI strategies, design end-to-end architectures and support the successful deployment of large language model applications.

The ideal candidate must have hands-on experience building and deploying production machine learning or generative AI systems—not only designing general cloud infrastructure or delivering high-level technical presentations.

Responsibilities

• Support the AI MaaS sales team in developing large enterprise AI opportunities and increasing the adoption and consumption of large language models.

• Engage with enterprise customers in business and technical architecture discussions to understand their requirements, identify AI opportunities and guide projects toward successful closure and deployment.

• Design end-to-end generative AI solutions covering data pipelines, model selection, model serving, application integration, production monitoring and continuous optimization.

• Develop architectures involving: Large language model deployment，Prompt engineering，Retrieval-Augmented Generation，Vector databases，AI agents，Workflow orchestration，Model fine-tuning，Inference optimization

• Design scalable AI infrastructure using GPU clusters, cloud computing resources, model registries, experiment-tracking platforms and machine learning CI/CD pipelines.

• Develop tailored technical demonstrations and proof-of-concept applications based on customer business scenarios.

• Translate customer requirements into secure, scalable and production-ready AI and cloud architectures.

• Recommend suitable AI models, cloud services and infrastructure based on performance, cost, security, scalability and data requirements.

• Support customers with AI application deployment, model API integration, cloud environment configuration and production troubleshooting.

• Present complex AI architectures and technical recommendations to enterprise CTOs, AI leaders, engineering teams and business decision-makers.

• Collaborate with internal AI product, engineering and algorithm teams to resolve critical technical issues and convert customer feedback into actionable product requirements.

• Monitor developments in large language models, AI agents, MaaS platforms, model fine-tuning, inference technologies and enterprise AI applications.

Qualifications

• Bachelor’s degree or higher in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Data Science, Software Engineering or another related STEM discipline.
• Master’s degree or PhD in a relevant technical field is preferred.
• 5–12 years of professional experience in solutions architecture, with deep specialization in machine learning, artificial intelligence or generative AI.
• Demonstrable hands-on experience building and deploying production-grade machine learning or generative AI systems.
• Strong practical experience with the generative AI technology stack, including: LLM deployment，Model fine-tuning，Inference optimization，Vector databases，RAG architectures，AI agent development.
• Strong MLOps and AI infrastructure background, including experience with: GPU clusters,Model registries,Experiment tracking,CI/CD pipelines for machine learning, Model serving, Production monitoring.
• Ability to design end-to-end cloud-based generative AI solutions, from data ingestion and processing through model deployment and production operations.
• Experience with leading large language models such as Qwen, Gemini, Claude, OpenAI models or other commercial and open-source models.
• Experience with AI frameworks and platforms such as LangChain, LlamaIndex, Hugging Face, Dify, n8n, MCP or similar tools.
• Strong understanding of public cloud and AI infrastructure, including compute, GPU resources, storage, networking, databases and DevOps practices.
• Experience presenting technical AI architectures to enterprise CTOs, AI leaders and senior technical decision-makers.
• Strong customer-facing communication, technical consulting and problem-solving skills.
• Ability to communicate complex AI concepts clearly to both technical and non-technical stakeholders.
• Fluent German and English are required.
• Must hold a valid German or EU work permit. Visa sponsorship is not available.
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