AI Security Engineer

Allegis Group Singapore Pte Ltd

Singapore

On-site

SGD 120,000 - 180,000

Full time

3 days ago
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Job summary

Allegis Group Singapore Pte Ltd is seeking an experienced AI Security Consultant to join a greenfield initiative focused on building enterprise-scale AI security capabilities. You will design and implement AI guardrails that provide centralized, consistent, and auditable protection for AI-enabled applications in a cloud-native environment.

Working with security, cloud, and platform teams, you will assess risks, conduct threat modelling, architecture reviews, and secure design sessions, helping

Qualifications

  • 5+ years' experience in Cyber Security or related field.
  • 1+ years' hands-on AI Security experience.
  • Experience securing LLMs (GPT, Claude, etc.) and AI threats.
  • Hands-on with AI Guardrails and threat modelling.
  • Experience with AWS/Azure/GCP AI services.
  • Strong Python skills; familiarity with Java/Go/C#/C++.
  • Experience with APIs, DevSecOps, CI/CD, IaC, Docker, and Kubernetes.
  • Strong stakeholder management and documentation skills.

Responsibilities

  • Design and implement AI security guardrails for enterprise AI and Generative AI applications.
  • Assess and mitigate AI-specific security risks, including prompt injection, data leakage, model poisoning, and model theft.
  • Conduct AI security assessments, threat modelling exercises, architecture reviews, and secure design reviews.
  • Support the deployment and security of AI platforms leveraging cloud technologies, Kubernetes, and containerized environments.
  • Collaborate with engineering and platform teams to establish AI governance frameworks, security standards, and operational processes.
  • Evaluate and secure Large Language Models (LLMs) and AI-powered applications across the development lifecycle.
  • Integrate security controls into DevSecOps pipelines and cloud-native deployments.
  • Produce architecture documentation, security assessments, technical designs, and process documentation.
  • Partner with stakeholders across security, engineering, architecture, and business teams to drive secure AI adoption.

Skills

Cyber Security
AI Security
LLMs Security
Python
DevSecOps
Docker
Kubernetes
APIs
CI/CD
IaC
Stakeholder Management
Documentation

Tools

AWS Bedrock
SageMaker
Azure AI Foundry
Azure ML
Vertex AI

Job description

  • Design and implement AI security guardrails for enterprise AI and Generative AI applications.
  • Assess and mitigate AI-specific security risks, including prompt injection
  • Conduct AI security assessments, threat modelling exercises, architecture reviews, and secure design reviews
About the Role

We're seeking an experienced AI Security Consultant to join a greenfield initiative focused on building and deploying enterprise-scale AI security capabilities. This role will play a key part in designing and implementing AI Guardrails that provide centralized, consistent, and auditable protection for AI-enabled applications across the organization.
Working closely with security, cloud, and platform engineering teams, you'll help establish the foundational security controls, governance frameworks, and architecture required to securely scale Generative AI and Agentic AI solutions in a cloud-native environment.

Key Responsibilities
  • Design and implement AI security guardrails for enterprise AI and Generative AI applications.
  • Assess and mitigate AI-specific security risks, including prompt injection, data leakage, model poisoning, model theft, supply chain vulnerabilities, and agentic AI threats.
  • Conduct AI security assessments, threat modelling exercises, architecture reviews, and secure design reviews.
  • Support the deployment and security of AI platforms leveraging cloud technologies, Kubernetes, and containerized environments.
  • Collaborate with engineering and platform teams to establish AI governance frameworks, security standards, and operational processes.
  • Evaluate and secure Large Language Models (LLMs) and AI-powered applications across the development lifecycle.
  • Integrate security controls into DevSecOps pipelines and cloud-native deployments.
  • Produce architecture documentation, security assessments, technical designs, and process documentation.
  • Partner with stakeholders across security, engineering, architecture, and business teams to drive secure AI adoption.
Required Experience & Qualifications
  • 5+ years' experience in Cyber Security, Application Security, Cloud Security, Platform Security, or Secure Software Engineering.
  • 1+ years' hands-on experience in AI Security, GenAI Security, AI/ML Security, or AI Application Security.
  • Experience securing LLMs (GPT, Claude, Gemini, Llama, etc.) and understanding AI-specific threats such as prompt injection, data leakage, model poisoning, and model theft.
  • Hands-on experience with AI Guardrails, AI Red Teaming, Threat Modelling, AI Risk Assessments, and Security Reviews.
  • Experience with Agentic AI solutions and Model Context Protocol (MCP) ecosystems.
  • Exposure to AWS Bedrock, SageMaker, Azure AI Foundry/Azure ML, or Google Vertex AI.
  • Strong Python skills, with experience in languages such as Java, Go, C#, or C++.
  • Experience with APIs, DevSecOps, CI/CD, Infrastructure as Code, Docker, and Kubernetes.
  • Strong stakeholder management, communication, and documentation skills.

We regret to inform that only shortlisted candidates will be notified.

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