Senior AI & Cloud Security Engineer

RAPSYS TECHNOLOGIES PTE LTD; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE LTD is seeking a Senior AI & Cloud Security Engineer to lead security across cloud and AI environments. You will model threats, review LLM architectures, and implement robust security controls throughout CI/CD and container pipelines.

Experience with AI/ML workloads, Kubernetes, and cloud platforms is essential. The role involves building automation, working with red teams, and translating emerging threats into practical security measures.

Qualifications

• 7+ years of hands-on security engineering experience in cloud/DevSecOps.
• Experience securing AI/ML workloads and Generative AI environments.
• Strong knowledge of CI/CD security, container security, IaC, and software supply-chain security.
• Familiarity with cloud security controls across identity, network, data protection, and logging.
• Exposure to OWASP guidance for AI/LLM apps, MITRE ATLAS, and NIST AI RMF.

Responsibilities

• Threat-model and security-review LLM apps, RAG architectures, and agentic workflows.
• Design and execute AI security testing and adversarial evaluations.
• Secure AI data supply chains including provenance and dependencies.
• Embed security into CI/CD through policy-as-code and automated testing.
• Design cloud security controls across identity, networking, and data protection.
• Build security automation and tooling using Python or similar languages.
• Serve as SME for AI/cloud security incidents and remediation.

Skills

Threat modelling

LLM security

Adversarial testing

CI/CD security

Container security

IaC security

Python

Security automation

Cloud security

Tools

Kubernetes

Job description

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.

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.


• 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.

Sensitivity Label: General