AI Engineer

• Advanced AI Model Development: Designing and optimizing machine learning models (supervised, unsupervised, and NLP-based) to drive security-focused intelligence across the platform.
• RAG & Embedding Workflows: Building and deploying RAG pipelines, embeddings, and feature stores that enable context-aware, real-time decision-making.
• Production-Ready AI Systems: Collaborating with Data and MLOps engineers to package, deploy, and monitor models in scalable, cloud-native environments.
• AI-Driven Analytics: Leveraging deep learning and NLP to provide actionable insights into risk posture, compliance, and security events.
• Future-Proofing for Quantum: Researching and prototyping AI approaches that can adapt to post-quantum cryptographic standards and automated remediation.
• Model Development & Optimization: Implement, refine, and maintain ML models (supervised, unsupervised, NLP-based models).
• Production Integration: Work with Data/MLOps engineers to package, deploy, and monitor models within a robust CI/CD pipeline.
• Performance Tuning: Optimize model efficacy, efficiency, and reliability.
• Parallel Project Support: Split or manage multiple AI initiatives to enable faster execution across various R&D efforts.

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