AI Security Engineer

V2 Solutions; Hyderabad; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

V2 Solutions is seeking an AI Security Engineer to secure AI/ML pipelines, generative AI apps, and agentic AI systems on Google Cloud Platform. The role blends traditional GCP security with AI-specific threat modeling and defense against model theft, prompt injection and data poisoning.

Key responsibilities include hardening Vertex AI and GKE for AI workloads, implementing DLP and data protection within pipelines, and building Python-based security tooling.

Qualifications

• 5-8 years in security engineering, ~3 years in AI/ML security or applied ML
• Hands-on with Vertex AI, GKE, Model Armor/Gemini
• Strong Python; familiarity with TensorFlow/PyTorch
• Understanding of adversarial ML techniques

Responsibilities

• Secure AI/ML pipelines against adversarial threats
• Implement Model Armor & Gemini Enterprise Security
• Secure agentic AI workflows & enterprise data access
• Harden Vertex AI & GKE for AI workloads
• Integrate DLP/SDP into training/inference pipelines
• Build Python-based security tooling
• Partner with ML teams for security-by-design
• Track OWASP LLM Top 10, MITRE ATLAS

Skills

AI/ML Pipeline Security

Adversarial ML Defense

Generative AI Security

GCP AI Infrastructure Security

Python

Secure Code Deployment

DLP / Sensitive Data Protection

Security-by-Design Collaboration

Threat Modeling

MITRE/OWASP Awareness

Tools

Vertex AI

GKE

Gemini Enterprise Security

Model Armor

TensorFlow

PyTorch

Job description

AI Security Engineer

Secure AI/ML pipelines, Generative AI apps, and agentic AI systems on GCP; blends traditional GCP security with AI-specific threats. 5070% AI security focus.

Primary Skills

• AI/ML Pipeline Security & Adversarial ML Defense (model theft, prompt injection, data poisoning)
• Generative AI & Agentic Security (Gemini Enterprise Security, Model Armor)
• GCP AI Infrastructure Security (Vertex AI, GKE)

Secondary Skills

• Python & Secure Code Deployment
• DLP / Sensitive Data Protection (data pipeline integration)

Key Qualifications

• Secure AI/ML pipelines against adversarial threats
• Implement Model Armor & Gemini Enterprise Security
• Secure agentic AI workflows & enterprise data access
• Harden Vertex AI & GKE for AI workloads
• Integrate DLP/SDP into training/inference pipelines
• Build Python-based security tooling
• Partner with ML teams for security-by-design
• Track OWASP LLM Top 10, MITRE ATLAS

Minimum Qualifications

• 5-8 years in security engineering, ~3 years in AI/ML security or applied ML
• Hands-on with Vertex AI, GKE, Model Armor/Gemini
• Strong Python; familiarity with TensorFlow/PyTorch
• Understanding of adversarial ML techniques

Preferred Qualification

• GCP certification (Security Engineer or ML Engineer) preferred