
Advanced Cybersecurity and AI Specialist
4 days ago
This is a high-level position that involves the design, development, and deployment of AI-driven security solutions. The ideal candidate will have expertise in both AI and cybersecurity, with a strong understanding of how to integrate these two fields to create robust security systems.
Key Responsibilities:- The successful applicant will be responsible for architecting and implementing scalable Generative AI features, including agentic workflows, conversational AI, and autonomous agents.
- They will also develop and deploy machine learning models for threat detection, anomaly detection, malware classification, and behavioral analysis.
- Applying best practices in AI security, including mitigation of hallucinations, prompt injection, and bias, will be a key part of this role.
- The individual will identify and mitigate risks related to adversarial machine learning, model inversion, data poisoning, and prompt injection.
- Large-scale security datasets (e.g., logs, network traffic, endpoint telemetry) will be analyzed to identify patterns and build predictive models.
- Researching and implementing AI and Machine Learning techniques to improve detection accuracy and reduce false positives will also be an important responsibility.
- Designing and implementing security controls for AI/ML systems, including model training, inference, and data pipelines, will be a critical task.
- Collaborating with security analysts and incident response teams to integrate AI tools into existing workflows will be essential.
- Collaboration with data scientists, ML engineers, and DevOps teams to integrate security into the AI/ML lifecycle will also be required.
Required Technical And Professional Expertise:
- Experience in full AI project lifecycle, from research and prototyping to deployment in production environments, is a must.
- Familiarity with Agile development methodologies is also essential.
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, or similar is necessary.
- Experience with AI and/or data governance is highly desirable.
- Building automation solutions with AI/ML is also a valuable skill.
- Knowledge of AI ethics, fairness, and explainability is crucial.
- A strong understanding of cybersecurity principles, threat landscapes, and common attack vectors is required.
- Experience with threat modeling and securing cloud-based AI infrastructure (e.g., AWS, Azure, GCP) is a plus.
- Experience with data engineering and working with large-scale datasets is also highly valued.
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