We are looking for talented Senior Cybersecurity R&D Engineer who can bridge the worlds of AI and information-security. The ideal candidate will have relevant R&D experience in either or both 1) applying state-of-the-art
AI techniques to strengthen cyber-defense
(e.g. Deep Learning-based intrusion detection) and/or 2) in
securing AI systems themselves
(adversarial robustness, LLM guardrails, model privacy, data-exfiltration detection, etc.). This role will lead cutting-edge research projects, translate findings into production-grade solutions, and mentor a growing team of security researchers.
Key Responsibilities:
Conceive, design, and execute advanced R&D initiatives that fuse AI/ML with cybersecurity, including but not limited to: adversarial attack/defense, LLM prompt guardrails, privacy preserving inference, and zero trust micro service security.
Work closely with cross-functional teams, including software developers, network engineers, data scientists or AI engineers, to integrate research insights into practical applications.
Contribute to multiple projects simultaneously, ensuring timely delivery and achievement of project goals.
Provide guidance and mentorship to junior researchers and team members, fostering their professional growth and development.
Qualifications:
Master's degree in Computer Science, Software Engineering, Electrical Engineering, Applied Mathematics or a closely related discipline.
A PhD in relevant field will be highly valued.
Experience:
Minimum of 3-5 years of relevant experience in academia or industry.
Proven track record of successfully leading or contributing to R&D activities.
Skills:
Proficient in Python (with TensorFlow, PyTorch, JAX), C/C++ or Rust for security tooling.
Experience with Docker, Kubernetes, and CI/CD pipelines for ML model deployment.
Familiarity with network protocols, cryptographic primitives, secure coding practices, and threat modeling frameworks (e.g. STRIDE).
Understanding of compliance standards (e.g. ISO *****, NIST CSF, GDPR, CCPA) as they relate to AI systems.
Proefficiency in statistical analysis, hypothesis testing, and rigorous reproducibility practices.
Ability to design controlled adversarial experiments, evaluate model robustness, and conduct systematic security assessments.
Strong interpersonal skills to work effectively within a multidisciplinary team environment.
Innovative and critical thinking abilities to address research and technical challenges in modern Telecommunications systems, including the integration of AI-enabled solutions.
Ability to design controlled adversarial experiments, evaluate model robustness, and conduct systematic security assessments.
Very good written and verbal communication; ability to translate complex security concepts for non technical stakeholders.
Strong teamwork mindset, comfortable leading interdisciplinary groups and mentoring early career researchers.
Application:
Send your application to
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