AI Security Engineer

U3 INFOTECH PTE. LTD.; Singapore; On-site; SGD 140,000 - 190,000; Full time

Job summary

U3 INFOTECH PTE. LTD. is seeking a senior cybersecurity professional to lead and operationalize AI security across enterprise AI deployments.

The role focuses on securing AI systems, including large language models, and implementing guardrails, threat modeling, and secure DevSecOps practices in a cloud-native environment. You'll work with AWS Bedrock/SageMaker, Azure AI, or Google Vertex AI, and contribute to architecture design, risk assessments, and governance for enterprise-scale AI security

Qualifications

• Minimum 6 years of experience in cybersecurity, application security, cloud security, platform security, or secure software engineering.
• Minimum 2 years of hands-on experience in AI Security, Generative AI Security, AI application security, or AI/ML security within an enterprise environment.
• Hands-on experience securing AI systems and Large Language Models (LLMs), including GPT, Claude, Llama, Gemini, or equivalent models.
• Strong understanding of AI security risks and controls, including prompt injection, data leakage, model poisoning, insecure output handling, model theft, supply chain risks, and agentic AI threats.
• Hands-on experience with AI Security Guardrails, AI Red Teaming, AI Model Scanning, AI risk assessments, and threat modeling.
• Hands-on experience designing, developing, assessing, or securing Agentic AI systems and Model Context Protocol (MCP) ecosystems.
• Experience with Cloud AI platforms such as AWS Bedrock, AWS SageMaker, Azure AI Foundry/Azure ML, or Google Vertex AI.
• Strong programming and scripting skills in Python and at least one additional language such as Java, Go, C#, or C++.
• Strong understanding of REST APIs, JSON, authentication protocols, and API security.
• Experience in conducting security assessments, threat modeling, security architecture reviews, and secure design reviews.
• Experience with DevSecOps practices, CI/CD pipelines, Infrastructure as Code (IaC), GitHub/GitLab, automated security testing, and cloud-native deployments.
• Experience with container and orchestration technologies such as Docker and Kubernetes.
• Knowledge of SAST, DAST, SCA, secrets management, software supply chain security, and secure software development practices.
• Ability to produce architecture designs, security assessments, technical documentation, and process flows.
• Strong stakeholder management, communication, collaboration, and problem-solving skills.
• Possess positive learning and collaborative mindset.
• Good written and verbal communication skills.
• Agile, fast learner and able to adapt to changes.

Skills

Cybersecurity

Application security

Cloud security

Platform security

Secure software engineering

AI Security

Generative AI Security

AI model security

AI Guardrails

Threat modeling

Model scanning

MCP ecosystems

Python

Java

Go

C#

REST APIs

API security

CI/CD

IaC

GitHub

GitLab

Kubernetes

Docker

Job description

Summary:

• The project delivers an enterprise AI Guardrails capability to provide centralized, consistent, and auditable runtime protection for AI-enabled applications.
• Deployment of AI Guardrails by leveraging AWS EKS to manage the control plane while hosting the inference data plane on GPU enabled compute for high-performance model execution.
• The solution will include a unified administration console and a multi-AZ, high-availability deployment architecture. Key deliverables encompass the deployment topology, governance framework, and foundational platform setup with native integration with AI Gateway to support enterprise-scale operations.

Skillset Requirements:

• Minimum 6 years of experience in cybersecurity, application security, cloud security, platform security, or secure software engineering.
• Minimum 2 years of hands-on experience in AI Security, Generative AI Security, AI application security, or AI/ML security within an enterprise environment.
• Hands-on experience securing AI systems and Large Language Models (LLMs), including GPT, Claude, Llama, Gemini, or equivalent models.
• Strong understanding of AI security risks and controls, including prompt injection, data leakage, model poisoning, insecure output handling, model theft, supply chain risks, and agentic AI threats.
• Hands-on experience with AI Security Guardrails, AI Red Teaming, AI Model Scanning, AI risk assessments, and threat modeling.
• Hands-on experience designing, developing, assessing, or securing Agentic AI systems and Model Context Protocol (MCP) ecosystems.
• Experience with Cloud AI platforms such as AWS Bedrock, AWS SageMaker, Azure AI Foundry/Azure ML, or Google Vertex AI.
• Strong programming and scripting skills in Python and at least one additional language such as Java, Go, C#, or C++.
• Strong understanding of REST APIs, JSON, authentication protocols, and API security.
• Experience in conducting security assessments, threat modeling, security architecture reviews, and secure design reviews.
• Experience with DevSecOps practices, CI/CD pipelines, Infrastructure as Code (IaC), GitHub/GitLab, automated security testing, and cloud-native deployments.
• Experience with container and orchestration technologies such as Docker and Kubernetes.
• Knowledge of SAST, DAST, SCA, secrets management, software supply chain security, and secure software development practices.
• Ability to produce architecture designs, security assessments, technical documentation, and process flows.
• Strong stakeholder management, communication, collaboration, and problem-solving skills.
• Possess positive learning and collaborative mindset.
• Good written and verbal communication skills.
• Agile, fast learner and able to adapt to changes.