AI Security Engineer

TEKsystems Global Services, LLC; Singapore; On-site; SGD 140,000 - 190,000; Full time

Job summary

Allegis Group Singapore Pte Ltd is seeking an experienced AI Security Consultant to join a greenfield initiative focused on enterprise-scale AI security capabilities. This role designs and implements AI guardrails to provide centralized, auditable protection for AI-enabled applications across the organization.

Working with security, cloud, and platform engineering teams, you will establish foundational security controls, governance frameworks, and architectures to securely scale Generative AI in

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.

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.

Skills

Python

Stakeholder management

Communication

Tools

Docker

Kubernetes

AWS Bedrock

SageMaker

Azure AI Foundry

Vertex AI

CI/CD

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.

EA Registration :

Jun Wei Yap, R25126752

Allegis Group Singapore Pte Ltd, Company Reg No. 200909448N, EA License No. 10C4544