Senior AI Engineer: Production-Scale ML & AI Apps (Hybrid)

RHI Magnesita; Wien; Hybrid; EUR 59.000 - 72.000; Vollzeit

Benefits dieser Stelle

Annual transport pass

Home office up to 50%

Café & daily meal allowance

Global benefits platform

Zusammenfassung

RHI Magnesita in Vienna seeks a hands-on Senior AI Engineer to design, build, and scale the Smart Solutions AI portfolio across Europe & CIS. You will own architecture for data products, ML deployments, and agentic AI applications that touch production, sales, and enterprise systems.

You will develop and productionize ML solutions, leverage Databricks and cloud tools, and ensure robust evaluation and monitoring in a production setting for real business value.

Qualifikationen

• Several years of experience building data and machine learning systems that run in production, including responsibility for their operation after deployment.
• Expert Python and strong SQL, together with solid software engineering practices such as version control, automated testing, CI/CD, and cloud deployment.
• Experience with modern data platforms and distributed data processing; Databricks experience is an advantage.
• Demonstrable depth in at least one of the following areas: Commercial and customer data science: customer and product data, entity resolution, propensity or recommender models, forecasting, or NLP on business documents.
• Industrial and time-series data: sensor and process data, forecasting, anomaly detection, predictive modelling, or data-quality challenges in operational environments.
• Experience building and operating LLM-based applications with real users – for example retrieval, extraction, search, or tool-calling systems, and ideally agentic systems involving orchestration, delegation, and supervision of AI agents – together with systematic evaluation of their behavior and output quality.
• Strong judgement in solution design – including choosing the right level of technical complexity for the problem, knowing when a simpler statistical, ML, or workflow-based approach is preferable, and balancing solution quality with security, performance, and efficient model and token usage.
• Ability to understand commercial and operational business problems and communicate effectively with both technical and non-technical stakeholders.

Aufgaben

• Designing and building reliable data products and pipelines integrating production, machine, commercial, and enterprise data across multiple systems and sites, alongside less structured sources such as operational and service reports, business documents, internal communications, and external market data.
• Developing and productionize ML solutions such as forecasting, anomaly detection, predictive maintenance, segmentation, propensity and recommendation models, and optimization.
• Building AI applications using LLMs, retrieval, document processing, search, and tool-calling, including agentic systems with orchestration, delegation, and supervision of AI agents, where they create clear business value.
• Designing and run systematic evaluation for AI applications and agents – task success, output quality, regression testing, and monitoring of agent behavior in production.
• Building out an open integration architecture connecting enterprise systems, communications, and external data, and integrate AI applications with platforms such as SAP, CRM, MES, planning, and maintenance systems – using controlled, permissioned access that respects existing system boundaries, with human approval gates before any action that writes back to an operational system.

Kenntnisse

Python

SQL

Spark

Databricks

MLflow

Azure

CI/CD

Docker

LLM apps

Data pipelines

Tools

Databricks

Delta Lake

MLflow

Azure DevOps

Docker

CI/CD

Jobbeschreibung

RHI Magnesita in Vienna seeks a hands-on Senior AI Engineer to design, build, and scale the Smart Solutions AI portfolio across Europe & CIS. You will own architecture for data products, ML deployments, and agentic AI applications that touch production, sales, and enterprise systems.

You will develop and productionize ML solutions, leverage Databricks and cloud tools, and ensure robust evaluation and monitoring in a production setting for real business value.