Senior AI & Cloud Security Engineer

About the Role

We are seeking a highly skilled Senior AI & Cloud Security Engineer to lead and enhance our security initiatives concerning cloud and AI technologies. This role presents a unique chance to develop resilient security solutions, safeguard essential assets, and participate in pioneering projects within a fast-paced environment based in Singapore.

Key Responsibilities

• Perform threat modeling and security assessments for Large Language Model (LLM) applications, Retrieval-Augmented Generation (RAG) architectures, and agentic workflows, addressing risks such as prompt injection attacks, data leakage, unsafe tool usage, and excessive automation autonomy.
• Design and carry out AI security testing and adversarial evaluations, collaborating with expert red teams when necessary.
• Ensure security throughout AI and data supply chains, including management of model provenance, artifact tracing, dependencies, vector stores, reference data, and third-party integrations.
• Incorporate security practices into Continuous Integration/Continuous Deployment (CI/CD) pipelines via policy-as-code, automated security testing, container and Infrastructure-as-Code (IaC) scanning, plus vulnerability management.
• Architect and apply cloud security measures covering identity management, network segmentation, secrets and key management, data encryption, logging, and audit mechanisms.
• Develop security automation tools and assessment capabilities using Python or equivalent programming languages, replacing manual procedures with repeatable engineering controls.
• Serve as a technical subject matter expert for AI and cloud security incidents, conduct architectural reviews, support engineering remediation efforts, and translate emerging security threats into practical control measures for internal and client teams.

Qualifications and Skills

• At least 7 years of practical experience in security engineering, application security, cloud security, DevSecOps, or comparable roles, particularly in protecting AI/ML or Generative AI workloads.
• Expertise in DevSecOps practices including securing CI/CD pipelines, container and Kubernetes configurations, infrastructure-as-code security, management of vulnerabilities, and software supply chain protection.
• Solid understanding of cutting-edge AI system architectures such as model APIs, RAG, vector or retrieval databases, orchestration frameworks, and AI agent technologies.
• Comprehensive knowledge of application and API security, identity and access management (IAM) or workload identity controls, secrets management, data protection, and cloud-native security strategies.
• Deep proficiency in at least one leading cloud platform (AWS, Azure, or GCP) with the ability to implement equivalent security patterns across multiple cloud environments.
• Familiarity with AI security and governance frameworks including OWASP recommendations for LLM/Generative AI, MITRE ATLAS, and NIST AI Risk Management Framework.
• Proficiency in Python or comparable programming languages for building security automation, testing, and assessment tools.
• Capability to independently manage complex security challenges starting from threat modeling and architectural design through to implementation, testing, and mitigation.

Preferred Experience

• Background in AI red-teaming or adversarial testing of LLM and agentic solutions.
• Experience securing enterprise-grade RAG implementations, vector databases, model access gateways, or AI orchestration platforms.
• Knowledge of policy-as-code, Software Bill of Materials (SBOMs), artifact tracking, cloud security platforms, or security telemetry tools.
• Experience working within consulting firms, regulated sectors, or large-scale enterprises.