Security Expert - AI & HPC Infrastructure (HLRS_13_2026)

Höchstleistungsrechenzentrum Stuttgart (HLRS)
Stuttgart

As one of Europe's leading facilities for high-performance computing, HLRS is a diverse community of scientists, engineers, and other professionals focused on discovering and developing new applications of powerful digital technologies and computer science methods.

Security Expert – AI & HPC Infrastructure

The High-Performance Computing Centre Stuttgart (HLRS) was founded as Germany's first federal high-performance computing (HPC) center. It operates one of the fastest supercomputers in the world. It offers various HPC solutions and services for universities, research institutions, and industry. Furthermore, HLRS is a worldwide leader in engineering and global system sciences. Staff scientists at HLRS investigate emerging technologies such as Artificial Intelligence (AI), Cloud Computing, and Quantum Computing (QC) towards realizing hybrid workflows and lowering the hurdle for non-experts using HPC technologies. In this context, HLRS is significantly involved in international and national research projects across the abovementioned research areas.

HammerHAI — The AI Factory for Industry and Science
The HammerHAI project establishes a European AI Factory at the High-Performance Computing Center Stuttgart (HLRS), supported by a strong consortium from Germany, to successfully meet the growing demand for artificial intelligence (AI) infrastructure across Europe. HammerHAI will be a one-stop shop for many AI users, focusing primarily on start-ups, small and medium-sized enterprises (SMEs), and large industrial companies, as well as supporting academic institutions and the public sector. It will offer tailored services and infrastructure to accelerate AI innovation and help develop a competitive AI ecosystem in Europe. The AI Factory is located in a region that is one of Europe’s powerhouses in manufacturing and engineering innovation, and it integrates into an ecosystem that promotes talent building that will be the basis of an ongoing digital transition.
The AI Factory HammerHAI will provide secure, scalable, and AI-optimized supercomputing resources to meet the needs of start-ups, SMEs, industry, and research institutions. Its infrastructure will enable users to easily migrate their AI applications from laptops or cloud environments to supercomputers, providing the computing power needed to develop large-scale AI models. Hereby, the AI Factory supports the entire AI lifecycle, from data preparation to model training, deployment, monitoring, and retraining, and provides a comprehensive package of services to ensure efficient and effective AI development and operation.

Securing the Future of AI Infrastructure in HPC
We seek a highly motivated Security Expert to design, implement, and maintain security frameworks for AI workloads and HPC infrastructure within the AI Factory HammerHAI at HLRS. This role is responsible for safeguarding sensitive data, ensuring compliance with relevant security standards, and proactively identifying and mitigating security risks across the AI Factory's systems and services. The successful candidate works closely with ML researchers, system administrators, software developers, and external stakeholders to establish and enforce security best practices across all layers of the AI infrastructure. This position requires deep expertise in IT and infrastructure security, and ideally hands-on experience with high-performance computing or AI environments.

In this context, we are looking for a

Security Expert – AI & HPC Infrastructure
(m/f/d, up to TV-L 13, 100%)
HLRS_13_2026

to work on HammerHAI with a strong team of security and HPC experts in close collaboration with ML engineers, system administrators and external partners.
This is a temporary position. Employment is limited in accordance with the legal regulations to the project's duration, which is 31.03.2028. The salary for this position is based on your personal qualifications up to the level of TV-L 13.

Your Responsibilities

  • Implement and maintain secure identity and access management (IAM) solutions using solutions such as Keycloak and eIDAS 2.0 frameworks, towards ensuring seamless single sign-on (SSO) across the HammerHAI ecosystem.
  • Design and implement robust multi-tenancy security models to ensure strict data and workload isolation between different industrial and research partners on shared GPU clusters in close cooperation with HPC vendors.
  • Develop and maintain the Information Security Management System (ISMS), ensuring all technical architectures align with the EU AI Act, GDPR, and NIST standards.
  • Develop and deploy advanced guardrails for LLM inference services to mitigate risks such as prompt injection, sensitive data leakage, and harmful content generation.
  • Establish a means to monitor and analyze system logs, network traffic, and application metrics to identify security incidents, unauthorized access, or anomalous model behavior.
  • Collaborate with DevOps and ML engineers to implement automated security gates within CI/CD pipelines for containerized ML stacks.

Your Profile

  • A Master’s or PhD in Computer Science, Cybersecurity, or a related field with a strong focus on infrastructure or cloud security.
  • Proven expertise in modern identity management (e.g., Keycloak, OIDC) and the architecture of secure, multi-tenant containerized environments (Kubernetes).
  • Strong understanding of AI-specific security vulnerabilities unique to LLMs and Generative AI, including experience with guardrail frameworks and adversarial testing.
  • Familiarity with information security standards (e.g., BSI IT-Grundschutz or ISO 27001) and the ability to translate technical security concepts into formal documentation.
  • Strong technical communication skills, both written and verbal, for collaborating within an interdisciplinary environment of researchers and industrial partners.
  • Problem-solving mindset with the ability to address and resolve issues effectively.
  • Proficiency in German is mandatory for this role, as you will be contributing towards the German-language ISMS documentation and compliance tasks.
  • Strong written and spoken English skills required.

What We Offer

  • A professional working environment in a friendly, highly motivated and collaborative international team.
  • Flexible working hours with a flextime model and the possibility of compensating for time off in addition to the regular 30 days of vacation.
  • Flexible work hours with currently up to 60% home office (upon request).
  • Attractive social benefits of the public service.
  • Subsidy of €25 per month for public transport and the possibility of job bike leasing.
  • Use the wide range of further education and training opportunities (e.g., soft skills, languages, specialist courses, leadership seminars) and the sports offers of the University of Stuttgart.
  • Fixed-term employment with salary and working conditions up to TV-L13.

Are you interested?

If you are passionate about security in the context of AI and HPC and want to contribute to a transformative European project, we encourage you to apply.
Please send us your application, including a motivation letter, resume, certificates and references, stating the reference number of the position “ HLRS_13_2026” in the subject line, preferred by e-mail to bewerbungen(at)hlrs.de , no later than 22 May 2026, as a single PDF file.

You will be working at HLRS within the High-Performance Computing Network - Production (HPCN) department, headed by Thomas Beisel. If you have any questions about this job offer, please e-mail Thomas.Beisel(at)hlrs.de

The University of Stuttgart invites women to apply for this job opening to strengthen the presence of female workers in the scientific areas. Full-time positions may generally be turned into part-time positions. Disabled people will have priority as long as they are equally qualified. The central administration of the University of Stuttgart will handle the recruitment process.
Information on the handling of applicant data following Art. 13 DS-GVO can be found at:

Veröffentlicht am 2026-04-29

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