Cybersecurity Engineer - Cloud, Ops (human)

NEURA Robotics; Riederich; Vor Ort; EUR 75.000 - 110.000; Vollzeit

Zusammenfassung

NEURA Robotics is seeking a Systems Security Engineer to secure cloud-native platforms, perform threat modeling, and lead secure architecture reviews across microservices and AI/ML pipelines.

You will own AppSec tooling (SAST/DAST/SCA), manage vulnerability remediation, and contribute to NIS2 compliance and incident response workflows within a highly collaborative robotics environment.

Qualifikationen

• Degree in Computer Science, Cybersecurity, or Software Engineering.
• Hands-on experience with cloud security and DevSecOps tooling.

Aufgaben

• Secure cloud-native platforms (AWS) with least-privilege IAM and network segmentation.
• Operate SAST/DAST/SCA tooling and container/IaC scanning in CI/CD.
• Conduct STRIDE threat modeling across microservices and AI/ML pipelines.
• Lead secure architecture reviews for cloud-native and AI-adjacent systems.
• Support NIS2 compliance and incident response workflows with proper documentation.

Kenntnisse

Python/Bash

Container security

Kubernetes security

IaC security scanning

AWS security tooling

SAST/DAST tooling

Threat modeling

Security architecture

Ausbildung

Bachelors in CS/Cybersecurity/Software Eng

Tools

Semgrep

SonarQube

ZAP/Burp

GitLab CI/CD

SageMaker/Triton/ONNX security

Jobbeschreibung

Our Systems Engineering Department turns market demands into safe, certifiable, and competitive robot systems — spanning software, hardware, safety, and certification. Join us to shape the next generation of human-robot systems and find extraordinary opportunities at the intersection of security, compliance, and cutting-edge robotics.

Your Mission & Challenges

• Secure Cloud-Native Platforms: Secure cloud-native platforms (AWS EKS, Lambda, API Gateway, IoT Core, S3) via least-privilege IAM, network segmentation, secrets management, and policy-as-code (Terraform/AWS Organizations).
• Own the AppSec Toolchain: Operate SAST (Semgrep/SonarQube), DAST (ZAP/Burp), SCA, and container/IaC scanning in GitLab CI/CD; extend coverage to Kubernetes manifests and supply chain.
• Drive Vulnerability Management: Run risk-based vulnerability management: CVSS + exploitability rating, SLA-driven remediation tracking, and structured closure evidence for internal KPIs and regulatory reporting.
• Perform Threat Modeling: Conduct STRIDE threat modeling across microservices, edge, and AI/ML inference pipelines; translate findings into architecture decisions.
• Support NIS2 Compliance: Own NIS2 Art. 21 measure documentation, incident notification workflows (24h/72h), and supply-chain security assessments for cloud dependencies.
• Define Secure Coding Standards: Define and enforce secure coding and API standards (Python, TypeScript, C++; OAuth2/OIDC, JWT) and deliver developer-oriented remediation guidance embedded in engineering workflows.
• Lead Secure Architecture Reviews: Lead secure architecture reviews for cloud-native and AI-adjacent systems; assess AI/ML pipeline security controls (SageMaker, Triton, ONNX) and model supply chain risks.
• Bridge to Embedded Security: Align cloud threat models and security controls with the embedded cybersecurity team to maintain end-to-end integrity from robot controller to cloud backend.

What We Can Look Forward To

• Education & Certification: Degree in Computer Science, Cybersecurity, or Software Engineering; OSCP or AWS Security Specialty is a differentiator.
• Track Record: 3–5 years in application or cloud security with demonstrated ownership of AppSec tooling and vuln management in a product environment — not advisory only.
• Security Fundamentals: Hands-on command of OWASP Top 10/ASVS, cloud security posture (AWS preferred), and DevSecOps tooling (SAST, DAST, SCA) — not just theoretical.
• Vulnerability Management Process: Proven vuln management lifecycle: CVSS + exploitability triage, SLA-driven closure, and audit-ready documentation.
• Regulatory Familiarity: Working knowledge of NIS2, EU CRA, ISO 27001, or IEC 62443; able to translate findings into compliance documentation for internal governance and external audit.
• Technical Skills: Python/Bash proficiency; hands-on with container and Kubernetes security, IaC scanning, and AWS governance tooling (Config, SCPs, GuardDuty).
• AI/ML Pipeline Exposure: Exposure to AI/ML pipeline security (SageMaker, Triton, ONNX) and model supply chain risks is a significant differentiator.
• Collaboration & Communication: Communicates security risk clearly to engineering and management; written outputs audit-ready. Interfaces effectively with embedded security, certification, and external auditors.