Cloud Security Engineer (LLM Security)

- Strong background in cloud security engineering, ideally with deep experience on AWS; Azure exposure is highly beneficial - Hands-on experience or working exposure in securing LLM/AI workloads, including model deployment, data flows, and runtime considerations - Proficiency with cloud-native security tooling (CSPM, CWPP, secrets management, logging/monitoring, container security) - Experience securing IaC and CI/CD pipelines using tools such as Terraform, CloudFormation, GitHub Actions, GitLab, or similar - Knowledge of IAM design, network security controls, encryption, secrets management, and cloud identity principles - Understanding of modern cloud architectures (serverless, microservices, managed AI/ML services) and their associated security risks - Ability to collaborate effectively with AI engineers, developers, and cloud teams to ensure secure implementation of AI workloads - Desirable: Experience securing GenAI, Agentic AI, vector databases, model APIs, or data pipelines used by LLMs - Desirable: Knowledge of responsible AI principles, model governance, or AI-specific threat modelling (e.g., adversarial ML, data poisoning, prompt injection) - Desirable: Background working in regulated industries such as Financial Services or Insurance - Desirable: Strong stakeholder communication skills, including the ability to influence engineering teams and articulate cloud/AI security risks clearly