Job description
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- Design, develop, and deploy AI solutions for threat intelligence, malware/phishing detection, vulnerability assessment, incident response automation, and intrusion detection.
- Conduct threat modeling, risk analysis, and implement automated detection strategies.
- Implement Retrieval-Augmented Generation (RAG) pipelines to improve contextual detection and generate actionable insights.
- Build intelligent agentic models for autonomous decision-making, real-time threat mitigation, and automated cybersecurity workflows.
- Integrate LLM-based solutions for natural language queries, automated reporting, and security advisories.
- Analyze large-scale datasets (logs, network traffic, endpoint telemetry) using generative models to detect anomalies and malicious patterns.
- Develop secure and scalable data pipelines for ingestion, processing, and storage of diverse security data.
- Document designs, model performance, and integration strategies, ensuring compliance with cybersecurity standards.
roven experience with LLMs, Generative AI, agentic architectures, and RAG systems in production.
- Strong programming skills in Python, Java, or C++, with frameworks like TensorFlow, PyTorch, Hugging Face, or LangChain.
- Solid understanding of cybersecurity fundamentals: network protocols, threat modeling, malware analysis, and intrusion detection.
- Experience in secure data engineering, handling sensitive datasets, and deploying models in cloud environments (AWS, Azure, GCP).
- Familiarity with SIEM platforms (Splunk, ELK Stack) and their integration with AI-driven solutions.
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