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Security Specialist

JOBLINE RESOURCES PTE. LTD.

Singapore

On-site

SGD 70,000 - 100,000

Full time

Today
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Job summary

A leading cybersecurity consulting firm in Singapore seeks an experienced professional to drive AI/ML security assessments and manage risks. You will develop security controls, oversee cloud security for AI workloads, and translate technical risks into business impacts. The ideal candidate will have extensive experience in cybersecurity, particularly in securing AI/ML platforms, and hold relevant certifications. This position offers a 6-month agency contract with potential for extension.

Qualifications

  • 3–8+ years of experience in cybersecurity, cloud security, or data security roles.
  • Demonstrated experience securing AI/ML platforms or agent-based systems.
  • Certifications such as CCSP, CISSP or cloud security specialties.
  • Excellent analytical and communication skills.
  • Experience with MLOps tools like SageMaker, Vertex AI, Azure ML.

Responsibilities

  • Conduct comprehensive security assessments of AI/ML systems.
  • Develop and implement security controls and governance frameworks.
  • Design secure cloud architectures for AI workloads.
  • Translate technical security risks into clear business impacts.
  • Work cross-functionally with AI engineers and compliance teams.

Skills

Experience in cybersecurity
Cloud security skills (AWS, Azure, GCP)
Knowledge of IAM principles
Analytical skills
Excellent communication skills
Understanding of AI threats

Education

Degree in Computer Engineering or related discipline

Tools

Docker
Kubernetes
AWS
Azure
GCP
Job description
Responsibilities

AI/ML Security Assessments & Risk Management

  • Conduct comprehensive security assessments of AI/ML systems, including data pipelines, model training environments, inference endpoints, and MLOps workflows.
  • Identify complex risks related to data privacy, data leakage, adversarial attacks, model poisoning, prompt injection, and misuse of AI technologies.
  • Evaluate threats across the AI lifecycle—from data collection to model retirement and define appropriate mitigation actions.
AI Governance & Security Controls
  • Develop and implement security controls, governance frameworks, and policies for end-to-end AI lifecycle management.
  • Support clients in complying with AI regulations, responsible AI principles, and data protection requirements (e.g., GDPR, NIST AI RMF).
  • Create strategic roadmaps and executive-level recommendations for secure AI adoption.
Cloud & Infrastructure Security for AI
  • Design secure cloud architectures for AI workloads across AWS, Azure, and GCP.
  • Implement best practices for IAM, encryption, secrets management, container security, network segmentation, and secure data storage.
  • Assess and secure APIs, microservices, and application components that support AI models and intelligent systems.
Identity & Access Management for AI Agents
  • Design IAM models for AI agents, including agent identities, delegated permissions, EPHEMERAL credentials, and cross-system trust boundaries.
  • Implement zero-trust principles for agent authentication, authorization, and privilege controls; develop patterns for scoped access, JIT (Just-In-Time) authorizations, short-lived tokens, and decoupled privilege elevation.
  • Integrate IAM systems with AI agent orchestration and establish access governance processes, including permission reviews, certifications, and usage monitoring.
Client Communication & Advisory
  • Translate technical security risks into clear business impacts that executive stakeholders can act on; prepare assessment reports, recommendations, threat models, and remediation plans for clients.
  • Work cross-functionally with AI engineers, data scientists, IT security, and compliance teams to deliver secure AI solutions.
Requirements
  • Degree in Computer Engineering or related discipline.
  • 3–8+ years of experience in cybersecurity, cloud security, or data security roles.
  • Demonstrated experience securing AI/ML platforms, models, pipelines, or agent-based systems; strong knowledge of cloud security (AWS, Azure, GCP), IAM, network security, encryption, and API security.
  • Understanding of AI threats such as adversarial ML, data contamination, and model theft; experience with container platforms (Docker, Kubernetes) and MLOps tools (SageMaker, Vertex AI, Azure ML, MLflow).
  • Excellent analytical and communication skills, with the ability to present findings to technical and non-technical audiences.
  • Certifications such as CCSP, CISSP, CCIE, AWS/Azure/GCP Security Specialty, or AI governance credentials.
  • Experience in responsible AI, AI policy, or AI compliance frameworks.
  • Background in security engineering, threat modeling, or red teaming for AI systems.
  • Experience working in consulting organizations or large enterprise security programs.

Shortlisted candidate will be offered a 6 months Agency contract employment, subject to extension.

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