Your Key Responsibilities
Lead AI red teaming execution including prompt injection, jailbreak and data exfiltration scenarios
Perform AI threat modelling across model, data, and application layers
Design and implement LLM guardrails and RAG security controls
Conduct ML pipeline and model lifecycle security reviews
Secure APIs and AI inference endpoints in cloud environments
Support incident response for AI-specific threats and exploitation attempts
Integrate security controls into AI/ML pipelines and DevSecOps workflows
Collaborate with SOC teams for AI workload detection and monitoring use cases
Skills and Attributes for Success
Solid understanding of ML/GenAI concepts (LLMs, embeddings, pipelines)
Hands-on experience in application security, API security and cloud security
Knowledge of AI attack surfaces (prompt, model, data layers)
Adversarial mindset with ability to simulate real-world attack scenarios
Understanding of OWASP Top 10 and LLM vulnerabilities
Working knowledge of MITRE ATT&CK; framework
To Qualify for the Role
36 years of experience in cybersecurity, application security or cloud security
Hands-on exposure to AI/GenAI security concepts or implementations
Experience in vulnerability assessment, red teaming or threat modelling
Working knowledge of cloud platforms (Azure/AWS)
Ideally, You’ll Also Have
Hands-on experience with AI security tools such as Garak, PyRIT, LLM Guard
Exposure to adversarial ML tools (ART, Foolbox)
Experience integrating security into MLOps/DevSecOps pipelines
Certifications in cloud or security domains (AZ-500, CEH, etc.)
What We Look For
A self-driven cybersecurity skilled with strong technical depth in AI security and the ability to independently drive security testing and implementation for enterprise AI workloads.
What We Offer
Prospect to work on advanced AI security engagements, exposure to global clients, and continuous learning in AI-led cyber defence and adversarial testing methodologies.
📌 Agentic Ai Developer Pan India Gds Location Hyderabad
🏢 EY
📍 Hyderabad