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AI Security Engineer

AI Security Engineer

Kofax

2 years

53 Lacs

hyderābād

Posted:1 month ago| Platform: GlassDoor logo

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Skills Required

ai security integrity data cybersecurity design risk model pipeline ml development training deployment tooling monitoring scanning software devops compliance logging governance regulations nist python tensorflow pytorch aws azure gcp engineering offset

Work Mode

On-site

Job Type

Part Time

Job Description

We are seeking a skilled and security-minded AI Security Engineer to join our team. In this role, you will be responsible for identifying and mitigating security risks in artificial intelligence systems, ensuring the confidentiality, integrity, and availability of AI models and data. You will work cross-functionally with data scientists, engineers, and cybersecurity teams to design, build, and maintain secure AI systems across their entire lifecycle.

Key Responsibilities

AI Threat and Risk Assessment: Identify and assess AI-specific threats, including adversarial attacks, data poisoning, model inversion, and data leakage.
Secure AI Pipeline Development: Implement security best practices throughout the AI/ML development lifecycle—from data ingestion and training to deployment and monitoring.
Tooling & Automation: Develop and deploy tools for automated threat detection, model monitoring, and vulnerability scanning in AI workflows.
Cross-functional Collaboration: Partner with software engineers, data scientists, DevOps, legal, and compliance teams to ensure secure and responsible AI development.
Monitoring & Incident Response: Establish real-time monitoring, logging, and incident response procedures for AI systems in production.
Compliance & Governance Alignment: Ensure alignment with relevant cybersecurity standards and AI-related regulations (e.g., ISO/IEC 27001, NIST, GDPR).

Required Skills

Proficiency in Python; experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of cybersecurity fundamentals and secure software development practices.
Experience with cloud platforms (AWS, Azure, or GCP) and securing cloud-native applications.
Familiarity with security tools (e.g., static/dynamic analyzers, monitoring tools, threat modeling platforms).
Experience building or securing large-scale ML infrastructure.
Knowledge of privacy-preserving ML techniques (e.g., differential privacy, federated learning).
Familiarity with AI governance, fairness, or explainability frameworks.

Required Experience

2–4 years of professional experience in cybersecurity, software engineering, or AI/ML system development
AI certificate or Diploma can offset 1 year of work experience
1+ years working directly on securing AI/ML systems or data pipelines

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Kofax

Software Development

Irvine California

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AI Security Engineer