Ref.-Nr.: DE20972
Schedule type: Full Time
Contract Type: Permanent Position
WHAT WE ARE LOOKING FOR * Design, implementation, and continuous development of the technical security architecture for large Kubernetes-based platform, software, and data infrastructures * Hands-on analysis, hardening, and security validation of Linux, container, and Kubernetes infrastructures—from the host through the cluster to the application * Conducting technical security assessments, penetration tests, and adversarial security tests against our own platforms and components to practically demonstrate vulnerabilities and realistic attack vectors * Security review and hardening of Infrastructure as Code, as well as integration of automated security checks, security gates, and Policy-as-Code mechanisms into CI/CD and DevSecOps processes * Securing Kubernetes environments, including RBAC, workload isolation, admission policies, network policies, secrets management, and runtime security * Helping to shape a secure software supply chain, including for dependencies, container images, artifacts, SBOM, signing, provenance, and trusted build and deployment processes * Analyzing and securing network connections and communication paths between platforms, data centers, external networks, and connected systems, including segmentation, firewalls, gateways, TLS/PKI, APIs, and machine-to-machine communication * Design and technical validation of identity, authentication, and authorization concepts for users, services, and workloads, as well as secrets, credentials, certificates, and key management * Ensuring the protection of data at rest, in transit, and during processing in close collaboration with platform and data engineering teams * Conducting threat modeling, vulnerability analysis, and technical validation of findings; deriving and implementing effective countermeasures * Further development of security monitoring, audit logging, and detection capabilities, as well as support for the technical analysis and resolution of security incidents * Participate in the security assessment of AI/machine learning infrastructures and AI-based applications, and implement security proofs of concept through to production-ready solutions WHAT QUALIFICATIONS YOU SHOULD HAVE * A degree in computer science, cybersecurity, IT security, software engineering, or a comparable practical qualification * Several years of hands-on experience in a technically oriented security role, e.g., as a Security Engineer, Platform Security Engineer, DevSecOps Engineer, or Penetration Tester * Very strong practical knowledge of Linux, networks, containers, and Kubernetes, as well as a solid understanding of modern cloud-native and platform architectures * Practical experience in securing Infrastructure as Code, CI/CD/DevSecOps processes, and Kubernetes environments * In-depth knowledge of network segmentation, TLS/PKI, IAM/RBAC, secrets, and credentials, as well as common authentication and authorization concepts * Experience with vulnerability analysis and penetration testing, as well as the ability to reproduce findings in practice, understand technical root causes, and implement appropriate countermeasures * Strong scripting or programming skills, e.g., in Python, Bash, Go, or a comparable language, particularly for automation and security testing * Ability to integrate security architecture with practical implementation and to collaborate effectively with platform, software, network, and data engineering teams * A structured, responsible work style and strong written and spoken English skills * Experience with red-team, blue-team, or purple-team approaches and adversarial testing in complex platform environments * In-depth knowledge of software supply chain security, e.g., SBOM, artifact signing, provenance, dependency security, or trusted build processes * Experience with Policy as Code, admission control, and runtime security, e.g., with OPA/Gatekeeper, Kyverno, Falco, or comparable solutions * Knowledge of security monitoring, detection engineering, and incident response in distributed Kubernetes or on-premises environments * Experience securing large data platforms, object storage, databases, or data-intensive systems * Knowledge of AI/machine learning security, e.g., protecting AI endpoints, training data, models, ML pipelines, or AI supply chains * Experience with highly secured, on-premises, edge, or intermittently disconnected infrastructures
A solid foundation and practical implementation experience are essential for this role. Additional specialized knowledge is expressly not a requirement.
Stärken und Erfahrungen zählen bei Rheinmetall, auch wenn vielleicht nicht alle aufgeführten Anforderungen vollständig erfüllt sind. Wir freuen uns auf Bewerber (m/w/d), die Lust haben, etwas zu bewegen und Verantwortung zu übernehmen. Wir legen Wert auf Individualität und Chancengleichheit. Schwerbehinderte Bewerber (m/w/d) werden bei gleicher Eignung besonders berücksichtigt.
WHAT WE OFFER YOU At our location in Bremen, we offer you:
CONTACT INFORMATION Contact Person: Ms Özge Demirkaya
For questions regarding your application, please use the contact form.
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