The agentic system security researcher will work with a blend of cutting-edge security, agentic AI, LLMs, network, and quantum technologies to shape the future of networking from a new unified system thinking perspective. The researcher will be driving innovations in ensuring the coherent behavior and collaboration within a federation of distributed autonomous systems; bring together agentic AI, LLMs, semantic models (such as knowledge graphs, APIs and ontologies) to create authenticity and trustworthiness  in autonomous systems; intent based management principles; AI native networks; and AI driven self-learning and self-optimizing systems. As part of their role, researchers perform studies, design, prototyping, testing and validation, with ownership and responsibility of research projects, processes and results. Researchers also contribute to intellectual property and scientific publications in selected high-impact journals.


 

Impact
Ph.D. degree in Telecommunications, Electrical Engineering, Informatics or Mathematics, OR a Master’s degree in the above fields with minimum 5-years of research experience.

Strong hands-on experience with applying AI/ML modeling techniques especially agentic AI and LLMs on real data sets, including data management, model training and re-training, model lifecycle management, model performance optimization, and dealing with model inaccuracies. System modeling skills including theoretical problem formulation and decomposition, model definition, architecture design, concept verification and validation. Experience with network technologies, especially cellular/mobile networks, TCP/IP, optical, content delivery, packet switching, networking protocols, cloud native software, cyber-security is appreciated. Knowledge on quantum communication, quantum key distribution and quantum security (including relevant ETSI QSC and QKD industry specification groups) is an advantage. Solid command of at least one programming language, preferably either Python for AI/ML OR Java for system design (additional knowledge of Java/Python, C++, C, and familiarity with Linux systems and frontend technologies such as JavaScript/Angular/WebGL is an advantage).

As part of a research team, he/she will collaborate on and be exposed to:

Research, prototyping and validation of secure federated network and service automation solutions using agentic AI, LLM knowledge representation and extraction techniques applied in real operational systems and environments. Natural language and intent based human-machine and machine-human interfaces, including trustworthy generative AI mechanisms to create and distribute knowledge and data. Generative system modeling and model-based automation using Digital Twins and Network Digital Twins including prominent use cases around system security and failure resiliency. Working across a broad range of technologies, devices and ideas with a practical, engineering-based, problem-solving focus. Engagement, close collaboration, and technology transfer to various Nokia business units.