🌟 We're Hiring: Senior AI & Cloud Security Engineer! 🌟

We are looking for an experienced Senior AI & Cloud Security Engineer to lead and strengthen our security initiatives across cloud and AI environments. This is a fantastic opportunity to shape robust solutions, protect critical assets, and contribute to innovative projects in a dynamic setting.

📍 Location: Singapore, Singapore
⏰ Work Mode: Work from Office
💼 Role: Senior AI & Cloud Security Engineer

What you will do

Threat-model and security-review LLM applications, RAG architectures, and

agentic workflows, including risks such as prompt injection, data leakage,
insecure tool use, and excessive agency
Design and execute AI security testing and adversarial evaluations, working
with specialist red-team teams where appropriate
• Secure AI and data supply chains, including model and artifact provenance,
dependencies, vector stores, grounding data, and third-party integrations
• Embed security into CI/CD through policy-as-code, automated security
testing, container and IaC scanning, and vulnerability management
• Design and implement cloud security controls across identity, network
segmentation, secrets and key management, data protection, logging, and
auditability
• Build security automation and evaluation tooling using Python or equivalent
languages, replacing manual checks with repeatable engineering controls
• Act as a technical SME for AI and cloud security incidents, architecture
reviews, and engineering remediation, while translating emerging threats into
practical controls for internal and client teams
What you bring
• 7+ years of hands-on experience in security engineering, application security,
cloud security, DevSecOps, or related roles, with practical experience
securing AI/ML or Generative AI workloads
• Strong DevSecOps experience covering CI/CD security, container and
Kubernetes security, infrastructure-as-code, vulnerability management, and
software supply-chain security
• Hands-on understanding of modern AI architectures including model APIs,
RAG, vector/retrieval systems, orchestration frameworks, and AI agents
• Strong knowledge of application and API security, IAM/workload identity,
secrets management, data protection, and cloud-native security controls
• Deep expertise in at least one major cloud platform such as AWS, Azure, or
GCP, with the ability to apply equivalent security patterns across cloud
environments

Sensitivity Label: General
• Familiarity with AI security and governance frameworks such as OWASP
guidance for LLM/Generative AI applications, MITRE ATLAS, and NIST AI
RMF
• Python or equivalent programming capability for security automation, testing,
and evaluation tooling
• Ability to independently own complex security problems from threat modelling
and architecture through implementation, validation, and remediation
Nice to have
• Experience with AI red-teaming or adversarial evaluation of LLM and agentic
applications
• Experience securing enterprise RAG, vector databases, model gateways, or
AI orchestration platforms
• Experience with policy-as-code, SBOMs, artifact provenance, cloud security
platforms, or security telemetry
• Experience working in consulting, regulated industries, or large enterprise
environments

Required skills

Threat modeling for LLMs, RAG architectures, and agentic workflows (e.g., prompt injection, data leakage, insecure tool use)AI security testing and adversarial evaluation (including AI red-teaming)Software and AI model supply-chain security (SBOMs, artifact provenance, dependencies, vector stores)DevSecOps: CI/CD security, policy-as-code, automated security testing, container and IaC scanning, vulnerability managementCloud security controls design and implementation (identity, network segmentation, secrets/key management, data protection, logging/auditability)Security automation and tooling using Python or equivalent programming languagesTechnical subject-matter expertise for security incidents, architecture reviews, and engineering remediation; translating threats into practical controlsContainer and Kubernetes security (runtime and orchestration security)Hands-on understanding of modern AI architectures: model APIs, RAG, vector/retrieval systems, orchestration frameworks, and AI agentsApplication and API securityFamiliarity with AI security and governance frameworks (OWASP guidance for LLMs/Generative AI, MITRE ATLAS, NIST AI RMF)Deep expertise in at least one major cloud platform (AWS, Azure, or GCP) and ability to apply equivalent patterns across clouds

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