Senior Cybersecurity R&D Engineer Instituto Pedro Nunes Coimbra November 4, 2025

The Pedro Nunes Institute - Association for Innovation and Development in Science and Technology (IPN) is a
- profit association that promotes innovation in the scientific and technological fields.

We are looking for a 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
  - 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 Ph
  D 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 Tensor
  Flow, Py
  Torch, 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. ISO27001, NIST CSF, GDPR, CCPA) as they relate to AI systems.
• Proficiency 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.
• 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.