Job description

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Type of employment

• Full-time
• 
  

workplace

Munich

Full job description

About the Job

IT Infrastructure and Information Security (IFIS) has started a global transformation program aimed at enhancing the IFIS organization, leveraging simplification, quality and services harmonization. A key pillar of this transformation is the adoption of Artificial Intelligence (AI) and Automation capabilities to improve operational efficiency, scalability, service quality and workforce productivity across the organization.

As AI Engineer, you will be part of the newly formed IFIS AI Automation team. You will own the end-to-end delivery of AI and Generative AI solutions (agents, RAG systems, predictive models, automation) for prioritized IFIS use cases — from the data pipelines and integrations that feed them, through to building, deploying and operating the solution in production.

What you do

• Design, build, test and deploy AI and Generative AI solutions (agents, RAG systems, automation, predictive/ML models) for prioritized IFIS use cases, including the data pipelines and integrations they depend on.
• Select the right tool for each problem (e.g. Azure AI Foundry, Copilot Studio, Claude, AllianzGPT, or other approved platforms), with a clear rationale on cost, performance and governance trade-offs.
• Build and maintain the data pipelines, models and storage structures (e.g. Azure Data Lake, Databricks) that support AI/ML solutions, ensuring data quality, lineage and availability.
• Productionize solutions with enterprise-grade reliability: monitoring, alerting, error handling, version control and CI/CD. Build modular, reusable components (e.g. document extraction, retrieval pipelines, data connectors, evaluation harnesses) that accelerate delivery of future initiatives.
• Ensure all deployed solutions comply with Allianz Group AI governance, data classification and security requirements, and support their registration in the relevant AI/RAI tooling.
• Collaborate with the Architecture Liaison and IFIS pillar engineers to ensure solutions are scalable, secure and well-integrated into the existing technology landscape.
• Support stakeholders with clear explanations of technical solutions and contribute to demos and adoption activities.

What you bring

• Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, Machine Learning or a related quantitative field.
• Up to 5 years of experience across AI/ML engineering and data engineering, including hands-on experience building Generative AI or LLM-based applications.
• Strong hands-on skills in Python and SQL, with experience in Spark and cloud AI/data platforms (e.g. Azure AI / Azure OpenAI, Azure Data Lake, Databricks, or equivalent).
• Practical experience with RAG architectures, vector databases, prompt engineering, AI agents and orchestration frameworks (e.g. LangChain, LlamaIndex).
• Working knowledge of ETL/ELT design, data modelling, and MLOps practices (model/version lifecycle management, monitoring, CI/CD).
• Understanding of AI governance, data classification and security requirements in a regulated environment.
• Strong problem-solving skills and the ability to translate business use cases into working, production-quality solutions; certifications (e.g. Azure AI Engineer Associate, Databricks ML Associate) are a plus.

What we offer

• We offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working incl. up to 25 days per year working from abroad.
• We believe in rewarding performance and our compensation and benefits package includes a company bonus scheme, pension, employee shares program and multiple employee discounts (details vary by location).
• From career development and digital learning programs to international career mobility, we offer lifelong learning for our employees worldwide and an environment where innovation, delivery and empowerment are fostered.
• Flexible working, health and wellbeing offers (including healthcare and parental leave benefits) support to balance family and career and help our people return from career breaks with experience that nothing else can teach.