- Agentic Framework Design: Design and implement intelligent, multi-agent AI systems capable of executing complex security analysis workflows and automated decision-making.
- Context Optimization: Analyze diverse security datasets to determine the most effective context, telemetry data, and threat intelligence to feed into AI agents to maximize decision accuracy and minimize false positives.
- Model Configuration & Integration: Evaluate, configure, and deploy a variety of state-of-the-art language models and AI architectures tailored for high-performance security use cases.
- Data Analysis & Performance Evaluation: Perform deep data analysis on security events and model outputs to continuously refine agent logic, benchmark performance, and optimize AI-driven detection mechanisms.
- Collaboration & Deployment: Partner with security research and engineering teams to integrate intelligent AI components into production systems seamlessly and securely.
Required Technical Skills
- AI & Agentic Systems: Proven experience building applications with modern AI architectures, advanced prompt engineering, and multi-agent orchestration frameworks.
- Model Management: Hands-on experience configuring, optimizing, and deploying diverse machine learning and language models.
- Data Processing & Analysis: Strong proficiency in Python and data analysis libraries to manipulate, clean, and extract insights from high-velocity data streams.
- Security Awareness: Familiarity with cybersecurity concepts, threat detection principles, or common security data formats (such as system logs, event tracking, or endpoint telemetry).
Preferred Qualifications & Advantages
- SLM & Local Deployment: Direct experience working with, optimizing, and deploying Small Language Models (SLMs) to run efficiently in local or resource-constrained environments.
- Analytical Thinker: Exceptional problem-solving skills with the ability to diagnose complex system behaviors and iteratively improve AI model performance based on data.
- Adaptability: Passion for staying at the absolute forefront of rapidly evolving AI technologies and applying them creatively to complex domains.
- Experience: 3+ years of professional experience in data science, AI engineering, or related technical fields, with a proven track record of deploying AI-driven solutions.
- Education: Bachelor’s degree in Computer Science, Data Science, Cybersecurity, or a related quantitative field (or equivalent practical experience) from a recognized and accredited university.
