Tap Growth ai
Senior AI & Cloud Security Engineer
Singapore, SG现场永久制全职
发布于 2026年9月11日
此职位以 EN 发布
🌟 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
职位概览
工作类型
全职
邮箱
recruiter@tapgrowth.ai
所需技能
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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