AI Solution Architect (m/f/d)
Indexed description
About The Role
As an AI Solution Architect at beON, you will design robust, scalable, and secure AI systems that connect industrial operations with intelligent decision-making. You will be responsible for developing and implementing complex AI system architectures, connecting OT and IT environments, and enabling data-driven operations — from edge devices and production systems to cloud infrastructure. Your focus will be on real-time monitoring, analytics, and model-driven automation in industrial environments. You will serve as the key technical link between OT, IT, and AI teams.
- Work Location: and/or , Hybrid, Düsseldorf, Deutschland
- Employment type: Permanent, Full-time
- Start: As soon as possible
- Language Requirements: English (German is a plus)
- Compensation: Competitive salary with performance-based bonus and advancement opportunities
- Design and implement scalable AI architectures in hybrid and cloud environments (Azure, AWS, GCP)
- Integrate production systems (SCADA, MES, DCS) and IIoT components using OPC UA, MQTT, and Modbus
- Develop secure, high-performance data pipelines from OT/edge environments to data lakes and cloud platforms
- Support real-time applications for monitoring, anomaly detection, early warning, and forecasting
- Define interfaces (REST/gRPC) and workflows for machine learning model deployment and orchestration (e.g., MLflow, Kubeflow)
- Collaborate with ML Engineers, Data Scientists, and DevOps teams to deliver full end-to-end AI solutions
- Use SQL for data modeling, transformation, and integration
- Contribute to data governance, lineage, and compliance (e.g., GDPR, ISO/IEC 27001)
- Several years of experience designing data-driven system architectures, ideally in an industrial environment
- In-depth knowledge of industrial protocols and OT/IT integration (e.g., SCADA, OPC UA, edge devices)
- Expertise in edge computing, network security, and infrastructure design
- Proficiency in SQL and familiarity with BI tools such as Power BI
- Experience with MLOps pipelines and AI lifecycle platforms (e.g., MLflow, SageMaker, Vertex AI)
- Hands-on project experience in industrial or manufacturing settings
- Familiarity with IoT platforms, edge AI, or SCADA/MES systems
- Knowledge of modern data platforms (e.g., Snowflake, Delta Lake, BigQuery)
- Experience with orchestration tools such as Apache Airflow or dbt
- Practical experience deploying AI services in edge computing environments
- Strong communication skills with the ability to translate complex technical requirements into actionable plans
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