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# Senior AI Platform & Research Infrastructure Engineer

- **Company:** Leibniz-Rechenzentrum der Bayerischen Akademie der Wissenschaften
- **Location:** Garching bei München, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, User Authentication, Computer Programming, Databases, Continuous Integration, DevOps, Distributed Systems, Middleware, Identity and Access Management, Python (Programming Language), Machine Learning, Metadata Standards, Open Source Technology, OpenAI, Software Engineering, Web Applications, Data Logging, Cloud Platform System, Large Language Models, Backend, Containerization, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations, Api Gateway
- **Published:** October 5, 2026
- **Apply:** https://www.adzuna.de/details/5910330611

## About the Role

Required/Minimum Qualifications

 * Master's degree (or equivalent) in Computer Science, Software Engineering, Artificial Intelligence, or a related field.

Other Requirements

 * Professional experience in software engineering and distributed systems.
 * Strong programming skills in Python, Go, or similar technologies.
 * Experience with APIs, databases, cloud-native technologies, containers, and Kubernetes.
 * Knowledge of authentication, authorization, identity management, and DevOps practices.
 * Strong analytical, communication, and collaboration skills.
 * Professional proficiency in English.

Additional or Preferred Qualifications:

 * Experience with AI platforms, LLMs, machine learning infrastructure, or model serving.
 * Knowledge of multi-tenant platforms, API gateways, federated IAM, and OpenAI-compatible APIs.
 * Experience with CI/CD, infrastructure automation, and platform operations.
 * Familiarity with metadata standards, FAIR principles, or research infrastructures.
 * Experience in higher education, research, public-sector, or open-source environments.

## Description

* Design, develop, and operate a federated AI platform and model management environment for universities and research institutions.
 * Develop web applications, APIs, backend services, and platform components for AI model lifecycle management.
 * Build and integrate AI middleware, model registries, API gateways, authentication services, and multi-tenant platform capabilities.
 * Implement governance, approval, deployment, monitoring, and automation workflows for AI services and models.
 * Develop and operate Kubernetes-based cloud-native infrastructure, including CI/CD, monitoring, logging, and automation.
 * Collaborate with research partners, platform operators, and stakeholders in a national research infrastructure environment.