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Tap Growth ai

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! 🌟

Join our team as a Senior AI & Cloud Security Engineer and play a key role in designing, implementing, and securing advanced cloud and AI solutions. We are looking for an experienced professional who is passionate about cybersecurity, cloud architecture, and emerging AI technologies to ensure the integrity and resilience of our systems.

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

What You'll Do:

About the role - “Senior AI & Cloud Security Engineer”

We are looking for a senior hands-on security engineer to secure AI applications, cloud platforms, and the engineering pipelines that connect them.

This role combines AI security, cloud security, application security, and DevSecOps, with a strong focus on LLM, RAG, and agentic workloads. You will work directly with engineering teams to identify risks, design practical controls, automate security checks, and help AI solutions move safely into production.

This is a senior individual-contributor role focused on technical leadership and delivery, not people management.

What you'll 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


Eager to build secure next-generation solutions? 🚀 Apply now and join us on this exciting journey!

职位概览

工作类型

全职

邮箱

recruiter@tapgrowth.ai

所需技能

AI/LLM security (threat modeling for prompt injection, data leakage, agentic risks)Adversarial evaluation and red‑teaming for AIAI and data supply-chain security (model/artifact provenance, dependencies)Retrieval-augmented generation (RAG) and vector store securityCloud platform security (AWS, Azure, or GCP)CI/CD security and policy-as-codeContainer and Kubernetes securityInfrastructure-as-Code (IaC) security and scanningVulnerability management and software supply-chain securityIdentity and Access Management (IAM) and workload identitySecrets and key managementApplication and API securitySecurity automation and tooling using Python or equivalentLogging, monitoring, and auditability for cloud environments

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