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
- Strong 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 professional with robust technical depth in AI security and the ability to independently drive security testing and implementation for enterprise AI workloads.
What We Offer
- Opportunity to work on advanced AI security engagements, exposure to global clients, and continuous learning in AI-led cyber defence and adve
📌 Agentic AI Developer (Bengaluru)
🏢 EY
📍 Bengaluru