Security Researcher: eBPF & AI

We are looking for a unique talent to bridge the gap between low-level system observability and high-level AI reasoning. You will sit at the intersection of our deep tech initiatives: actively developing our eBPF agent (Cimon) while simultaneously leading the charge on our AI innovation security research.

In this role, you will be the architect of our "security brain." You will write the low-level code that observes what is happening (eBPF/Golang) and build the AI models that understand, diagnose, and prevent issues (LLMs/Python).

Key Responsibilities

• The "Eyes": eBPF Development & Systems Engineering
• Lead the Cimon Agent: Spearhead the active development of our high-performance eBPF agent "Cimon" using Golang and C.
• Kernel-Level Innovation: Design and implement eBPF programs for deep observability, runtime security, and container monitoring.
• Performance Obsession: Write beautiful, highly efficient code that runs in the Linux kernel with minimal overhead.
• Community Leadership: Actively participate in the eBPF and open-source communities, contributing code and presenting technical deep dives at conferences.
• The "Brain": AI Innovation & Security Research
• AI-Driven Security Solutions: Architect and prototype models for:
• Automated Exploitability: Checking SAST/SCA findings for validity.
• AI Remediation: Automatically fixing Dockerfile misconfigurations and generating patches.
• Model Detection: Identifying AI models embedded within codebases.
• Benchmarking & Rigor: Design evaluation frameworks to measure model accuracy, false positives, and robustness in security contexts.
• Prompt Engineering: Shape prompt strategies and workflows to translate real-world security challenges into actionable AI logic.
• The Intersection: Collaboration & Evangelism
• Cross-Functional Leadership: Serve as the technical link between the AI development team and the core security engineering team.
• Thought Leadership: Author whitepapers, technical blogs, and deliver talks on the cutting edge of "AI for Systems Security."
• Mentorship: Guide engineers on best practices for both low-level systems design and AI integration.
  
  

• No Context Switching Cost: You won't just be researching; you will be building the tools you research. You control the data collection (eBPF) and the analysis (AI).
• Deep Tech Focus: This isn't a wrapper-API role. You will be dealing with kernel bypasses, memory safety, and LLM hallucinations all in the same week.
• Impact: Your work will directly power the next generation of automated security remediation.
  
  

• Systems: 3+ years of experience with Golang and Linux Kernel development (eBPF or Kernel modules).
• AI/ML: Hands-on experience with LLMs, prompt engineering, and Python-based data analysis.
• Security: Deep understanding of SAST/SCA tools (e.g., SonarQube, Bearer, Snyk) and Container Security (Docker, K8s, Trivy).
  
  

• Strong knowledge of Linux systems design, networking, and OS internals.
• Proficiency in Python (for AI research) and Go/C (for Agent development).
• Experience in analyzing container build pipelines and identifying vulnerability origins.
• Ability to distill complex topics (both kernel-level and AI-level) for diverse audiences.
  
  

• Experience with Rego/Open Policy Agent (OPA).
• Publications or presentations at venues like KubeCon, Black Hat, or AI conferences.
• Experience with Cloud Security (AWS/Azure/GCP) and Infrastructure-as-Code scanning.
• Experience fine-tuning models for specific code-generation or security tasks.