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 27001, 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 <endereço ocultado>
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