- Strong ability to apply threat modeling methodologies to complex AI and data‑driven systems
- Deep understanding of Agentic/AI/ML and GenAI architectures, including LLMs, RAG pipelines, embeddings, vector databases, and orchestration layers
- Ability to clearly articulate AI security risks and mitigations to both technical teams and client stakeholders
- Proven experience operating in multi‑industry, client‑delivery environments
- 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 stack—data 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.
Bachelor’s or Master’s degree in Computer Science, Cyber Security, AI/ML, Data Science, or related field
8+ years of overall experience in cyber security, secure architecture, or threat modeling roles with minimum 2 years’ experience in AI specific threat modelling
Hands‑on experience securing cloud‑based AI solutions (Azure, AWS, GCP, or equivalent)
Strong understanding of AI security, adversarial ML, data protection, and privacy‑by‑design principles
Familiarity with global frameworks and standards such as NIST AI RMF, NIST CSF, ISO/IEC security standards, and emerging AI regulations
Experience working with clients across highly regulated industries such as Insurance, Banking, Healthcare preferred