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AI2CYBER

Agentic AI agents protecting networks autonomously

AI Engineer - B2B

Applied Machine LearningUpdated on Nov 10
Full-timeRemote in GreeceNo salary listed

About the Job

Requirements

  • A Master's or PhD degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.
  • Strong proficiency in Python and experience with widely used machine learning libraries and frameworks.
  • Practical experience developing and implementing reinforcement learning algorithms.
  • Experience with OpenAI Gym, Gymnasium, or similar reinforcement learning environments.
  • Good understanding of machine learning principles, model training, optimisation, and evaluation.
  • Experience integrating large language models into software applications or AI-driven workflows.
  • Understanding of AI agents, multi-agent architectures, and agent orchestration concepts.
  • Familiarity with Message Control Protocol (MCP) and its use in connecting AI systems with external tools and data sources.
  • Knowledge of cybersecurity principles, tools, and techniques.
  • Experience working with containerised environments such as Docker.
  • Ability to write clean, modular, testable, and maintainable code.
  • Ability to work independently, manage technical responsibilities, and collaborate effectively with multidisciplinary teams.
  • Applicants must currently reside in Greece and already have an active, legally registered sole proprietorship in Greece, be legally able to provide professional software engineering, AI development, or related IT consulting services, issue valid invoices, and enter into a B2B consulting agreement.
  • Strong foundations in artificial intelligence, reinforcement learning, and software engineering; ability to translate complex problems into effective AI-driven solutions; experience developing production-oriented AI applications; independent problem-solving and sound technical judgement; analytical thinking and attention to detail; proactive evaluation of new AI technologies; accountability and ownership throughout the development lifecycle; and interest in applying advanced AI techniques to cybersecurity challenges.

Responsibilities

  • Design, develop, and optimise reinforcement learning algorithms to address complex real-world challenges.
  • Integrate large language models to enhance agent reasoning, threat intelligence, automated decision-making, and human-machine interactions.
  • Implement and extend Message Control Protocol integrations to connect AI applications with external tools, data sources, and services.
  • Develop modular AI architectures and support coordination between multiple intelligent agents.
  • Prototype innovative AI and reinforcement learning methods and transition successful prototypes into production-ready solutions.
  • Collaborate with engineering, data science, and product specialists to integrate and deploy machine learning and reinforcement learning models.
  • Design and conduct experiments to evaluate model performance, reliability, and effectiveness.
  • Apply appropriate experimental design, statistical analysis, and performance evaluation techniques.
  • Develop scalable, maintainable, and well-documented Python code.
  • Contribute to code reviews, automated testing, debugging, and technical documentation.
  • Identify and resolve complex software engineering and AI integration challenges.
  • Support the deployment, monitoring, and continuous improvement of AI-driven applications.
  • Consider security, performance, and reliability throughout the development lifecycle.
  • Handle proprietary technical information with discretion and professional confidentiality.

Desired Qualifications

  • Experience with Kubernetes, Kafka, and REST APIs.
  • Familiarity with cloud computing platforms such as AWS or Microsoft Azure.
  • Experience with DevOps practices and continuous integration/continuous delivery pipelines.
  • Experience with PyTorch, TensorFlow, Stable-Baselines3, Ray RLlib, or similar machine learning and reinforcement learning frameworks.
  • Experience developing large-language-model-powered agents, tool integrations, or multi-agent systems.
  • Practical experience implementing Message Control Protocol servers or clients.
  • Experience with distributed computing, asynchronous processing, or scalable AI architectures.
  • Familiarity with MLOps, experiment tracking, model deployment, and monitoring.
  • Experience applying AI or reinforcement learning to cybersecurity, threat detection, automated security operations, or intelligent decision-support systems.
  • Understanding of secure AI development and security risks associated with large-language-model-based applications.

About the Company

AI2CYBER

Agentic AI agents protecting networks autonomously

AI2CYBER creates autonomous cyber defense using Agentic AI. It develops intelligent agents that think, act, and adapt in real time to detect, simulate, and neutralize cyberattacks before they unfold. The agents learn from live environments, share intelligence across networks, and autonomously orchestrate defense strategies to evolve faster than human responses, forming a digital immune system that predicts attacker behavior, optimizes defenses, and maintains resilience under active assault. The company differentiates itself by deploying self-directing, network-wide agents that coordinate across partners and research institutions, enabling a proactive, adaptive security posture rather than reactive protection. Its goal is to establish self-defending infrastructure where security continuously learns, adapts, and defends proactively against threats.

Company size
Not listed
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
2023

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