virtual7 GmbH is seeking an AI Solution Architect to design and evolve the overall AI/ML architecture for complex enterprise environments, focusing on Microsoft Azure. The role combines ML engineering, RAG architectures, and MLOps to deliver secure, scalable, production-ready AI solutions, while leading interdisciplinary AI/ML engineering teams and advising stakeholders.
Responsibilities
Design and develop the AI/ML overall architecture as an enterprise AI platform with a focus on Microsoft Azure
Provide technical leadership for ML pipeline projects, including training, deployment, monitoring, and drift detection
Conceive and optimize RAG architectures with respect to chunking, retrieval, guardrails, and context orchestration
Define and drive MLOps strategies, including CI/CD for models, experiment tracking, and model registry
Technically lead and coordinate interdisciplinary teams of ML/AI, LLM, and MLOps Engineers
Advise internal and external stakeholders on AI architectures and present concepts to IT leadership and business units
Requirements
Strong experience with cloud-based AI/ML solutions, ideally Microsoft Azure (Azure Machine Learning, Azure OpenAI Service)
Practical MLOps experience with tools such as MLflow, Kubeflow, or Azure ML Pipelines
Experience building RAG architectures, prompt engineering, and working with vector databases
virtual7 GmbH is an IT consulting and software development company specializing in digital transformation solutions for the public sector. They provide customized IT services for federal, state, and local government authorities to modernize and simplify digital processes.
Knowledge of integrating and orchestrating language models, ideally with LangChain or LlamaIndex
Experience with CI/CD for ML applications and excellent Python skills
Practical experience with at least two common ML frameworks, e.g., scikit-learn, PyTorch, or TensorFlow
Experience building enterprise architectures in cloud environments
Several years of experience in ML/AI architecture or comparable technical tasks in enterprise environments
Very good German (C2 level) and good English skills
Nice to Have
Knowledge in adjacent areas such as data platforms, containerization, container orchestration, Infrastructure as Code, and observability (e.g., Databricks, Azure Data Factory, Azure Data Lake, Docker, Kubernetes, Terraform, Prometheus, Grafana, Application Insights)
Basic understanding of AI governance, Responsible AI, and security/privacy requirements in enterprise environments
Experience in a technical leadership or architecture role
Azure, AWS, or Google Cloud certifications
Experience in the energy sector or utility industry