S
Selby Jennings
AI Security Engineer - Quant
Skills
Deep LearningPythonGolangWeb3CybersecurityMachine LearningAISupply Chain
1 month ago
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Important information
Contract type:
Permanent
Location:
Shanghai, China
Work mode:
Onsite
Published on:
15 September 2026
What they need
What You Will Do
- Requirements Review & Security Design: Lead security reviews, threat modeling, and penetration testing for AI Agents. Design and implement defense mechanisms against emerging threats, including tool abuse, context contamination, data poisoning, and prompt injection.
- Automated Security Tooling: Design and develop AI-powered automated security detection tools. Utilize Machine Learning (ML) and Deep Learning (DL) techniques to enhance threat detection, anomalous behavior analysis, and vulnerability discovery efficiency.
- Security Operations & Auditing: Participate in building Agent behavior auditing and anomaly detection systems to identify runtime malicious behavior chains. Help construct an AI-driven Security Operations platform to automate alert triage, attack attribution, and incident response strategy generation.
- Security Guardrails Implementation: Co-design and implement Agent security guardrails, including input filtering, output sanitization, tool call permission controls, and sandbox isolation.
- Frontier Research & Adversarial Defense: Track and research cutting-edge security threats in the AI/Agent ecosystem (e.g., prompt injection, tool abuse, privilege escalation, data exfiltration, supply chain attacks). Explore, design, and deploy robust defense solutions tailored to real-world business scenarios.
Who You Are
- Experience: Minimum of 3 years of experience in security development or penetration testing, with at least 1 year dedicated to LLM/AI security offense and defense. Proven Red Teaming or real-world adversarial experience is highly preferred.
- Frameworks & Frameworks: Deep familiarity with security frameworks such as OWASP Top 10 for LLM and MITRE ATT&CK. Strong understanding of common AI attack vectors, adversarial logic, and mitigation strategies, paired with a strong passion for AI security.
- Domain Knowledge: Familiarity with the entire AI product lifecycle (design, development, deployment, and operations). Understanding of cloud-native threat detection and standard infrastructure security. Prior experience in Web3 security and defense is a strong plus.
- Technical Skills: Proficient in at least one programming language (e.g., Python, Go, C++). Capable of building custom security tools from scratch or heavily customizing/extending open-source security platforms.
- Soft Skills: Exceptional communication, collaboration, and project management skills. A self-starter with strong continuous learning capabilities, able to own projects independently and convert bleeding-edge research into practical production defenses.
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