Senior AI & Cloud ,Devops, Security Engineer

RAPSYS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE. LTD. is seeking a senior hands-on security engineer to secure AI applications, cloud platforms, and engineering pipelines. The role blends AI security, cloud security, application security, and DevSecOps with emphasis on LLM, RAG, and agentic workloads.

You will work with engineering teams to identify risks, design practical controls, automate security checks, and help AI solutions move safely into production. Strong collaboration and hands-on execution are essential.

Qualifications

• 7+ years of hands-on security engineering, focusing on AI/ML workloads and secure SDLC practices.
• Strong DevSecOps experience across CI/CD security, containers, Kubernetes, IaC, and software supply-chain security.
• Hands-on understanding of modern AI architectures including model APIs, RAG, vector stores, and AI agents.
• Deep knowledge of application and API security, IAM/workload identity, secrets management, data protection, and cloud-native controls.
• Experience with major cloud platforms (AWS, Azure, GCP) and cross-cloud security patterns.
• Familiarity with OWASP LLM guidance, MITRE ATLAS, and NIST AI RMF frameworks.
• Proficiency in Python or similar languages for security automation and tooling.

Responsibilities

• Threat-model and security-review LLM apps, RAG architectures, and agentic workflows.
• Design and execute AI security testing and adversarial evaluations with red-team coordination.
• Secure AI/data supply chains including provenance, dependencies, and third-party integrations.
• Embed security into CI/CD through policy-as-code, automated testing, and vulnerability management.
• Design and implement cloud security controls across identity, network, secrets, data protection, logging, and auditability.
• Build security tooling and automation in Python to replace manual checks with repeatable controls.
• Serve as SME for security incidents, architecture reviews, and remediation guidance.

Skills

Security engineering

DevSecOps

AI security

Cloud security

Threat modelling

Python scripting

CI/CD security

Tools

Kubernetes

Terraform

IaC tooling

Job description

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.

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
• 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