Key Requirements

AI Security (Mandatory)
- Deep understanding of AI and Machine Learning security concepts.
- Experience identifying and mitigating threats specific to Large Language Models (LLMs), including prompt injection, data poisoning, model manipulation, and data leakage risks.

Model Armor (Nice to Have)
- Understanding of Model Armor and its role as an AI-specific security layer.
- Knowledge of implementation steps, threat detection capabilities, and security policy enforcement mechanisms.

AI Project Experience (Mandatory)
- Proven hands-on experience implementing and managing security controls for AI/ML projects.
- Ability to discuss previous AI security projects, architecture, challenges, and security outcomes in detail.

Threat Detection & Response (Mandatory)
- Experience defining detection criteria for security threats.
- Solid understanding of incident response, alert tuning,



and managing false positives effectively.

Terraform (Mandatory)
- Hands-on experience with Terraform for Infrastructure as Code (IaC).
- Experience deploying and managing security infrastructure in cloud environments.

Python (Mandatory)
- Strong Python programming and scripting skills.
- Experience developing security automation, integrations, and AI-related applications.

Google Cloud Platform (Mandatory)
- Strong hands-on experience with Google Cloud Platform (GCP).
- Experience working with cloud security, IAM, networking, monitoring, logging, and AI/ML services on GCP.

Preferred Experience
- Securing Generative AI and LLM-based applications.
- Cloud Security and DevSecOps practices.
- AI governance and risk management frameworks.

📌 AI SecOps Engineer (Bengaluru)
🏢 Artech
📍 Bengaluru