- Company Name
- Morgan Stanley
- Job Title
- Cybersecurity DevOps Engineer
- Job Description
-
Job Title: Cybersecurity DevOps Engineer
Role Summary:
Lead adversarial testing of AI/LLM systems within a security testing platform. Collaborate with product leaders, AI/ML engineers, and DevOps teams to detect and mitigate risks such as evasion, prompt injection, and data leakage. Deploy, manage, and secure cloud infrastructure, container environments, and orchestration platforms while ensuring compliance with industry standards.
Expectations:
- Minimum 4 years of hands‑on cybersecurity experience (red teaming, penetration testing, application security, vulnerability management, compliance, governance).
- Proficiency in at least one programming/scripting language (Python, Java, C/C++, Bash).
- Solid command‑line skills in Linux and Windows.
- Deep understanding of threat actor TTPs, MITRE ATLAS, OWASP Top 10 for LLMs, and AI threat modeling.
- Experience with cloud security best practices across AWS, Azure, and GCP.
- Knowledge of containerization (Docker) and orchestration (Kubernetes).
- Strong analytical, problem‑solving, communication, and stakeholder management abilities.
Key Responsibilities:
- Operate and refine an adversarial testing platform for AI/LLM models.
- Identify, validate, and document security risks in AI/LLM pipelines (prompt injection, model evasion, data leakage).
- Work with AI/ML and application developers to embed security controls into model training and inference stages.
- Deploy and maintain cloud resources, ensuring secure architecture and configuration.
- Conduct regular security assessments, pen tests, and compliance audits.
- Communicate findings and improvement opportunities to product leads and technical teams.
- Develop and maintain scripts/tools for automated testing and monitoring.
Required Skills:
- Cybersecurity technologies & operations (red team, pen testing, vuln management, compliance)
- Programming/scripting: Python, Java, C/C++, Bash
- Operating systems: Linux, Windows (CLI)
- Cloud platforms: AWS, Azure, GCP (security features, IAM, networking)
- Containerization: Docker; Orchestration: Kubernetes
- AI/LLM concepts: prompt engineering, fine‑tuning, retrieval‑augmented generation (RAG)
- Security frameworks: MITRE ATLAS, OWASP Top 10 (LLM)
- Threat intelligence, TTPs, threat modeling
- Data analysis & reporting
- Stakeholder communication
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Cybersecurity, or related field.
- Professional certifications preferred: CISSP, CEH, CISM, GCP/AWS Security Specialty, or equivalent.
- Willingness to obtain any mandatory regulatory or internal corporate qualifications as required.