Senior Manager-AI Threat Modelling

We are hiring a Senior Manager AI Threat Modeling to lead security assessments for AI/ML, Generative AI, LLM, RAG, and Agentic AI solutions.

Key Responsibilities

• Lead AI threat modeling initiatives across enterprise and client-facing Agentic and AI solutions, including traditional ML, GenAI, LLMs, and agentic AI systems.
• Identify and assess threats across the AI stackdata pipelines, training processes, model artifacts, inference layers, APIs, integrations, and infrastructure.
• Analyze risks such as data poisoning, model theft, prompt injection, inference attacks, hallucination exploitation, supply-chain compromise, and misuse/abuse scenarios.
• Develop and maintain AI-specific threat models, abuse cases, and attack scenarios tailored to different client industries and deployment models.
• Embed threat modeling into the AI solution lifecycle, from design and build through deployment, scaling, and ongoing monitoring.
• Partner with engineering, data science, cloud, and platform teams to define security requirements, control recommendations, and architectural guardrails.
• Support client engagements, including security reviews, architecture assessments, and risk discussions related to AI solutions.
• Contribute to secure AI reference architectures, standards, and reusable patterns for enterprise and client delivery teams.
• Support AI security incident analysis, lessons-learned exercises, and control improvements where applicable.
• Stay current on emerging AI threat vectors, adversarial techniques, and industry research, translating insights into practical guidance for delivery teams and clients.

Required Skills

• 8+ years of experience in Cyber Security, Security Architecture, Threat Modeling, or related domains.
• 2+ years of experience in AI/GenAI Security or AI Threat Modeling.
• Strong understanding of LLMs, RAG, Embeddings, Vector Databases, and Agentic AI architectures.
• Experience with Threat Modeling methodologies (STRIDE, Attack Trees, Abuse Cases).
• Knowledge of AI security risks including Prompt Injection, Data Poisoning, Model Extraction, and Adversarial ML.
• Hands-on experience with Azure, AWS, or GCP.
• Familiarity with NIST AI RMF, NIST CSF, ISO 27001, and AI governance frameworks.
• Strong stakeholder management and client-facing consulting experience.