Manager - AI Security Engineer

6 - 10 years

14 - 19 Lacs

Posted:1 day ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Job Title: AI Security Engineer

Location:

Role Overview

AI Security Engineer

Key Responsibilities

  • Secure

    LLMs, ML models, NLP systems, and deep learning pipelines

  • Identify and mitigate AI risks including

    prompt injection, data leakage, model poisoning, hallucination misuse, and unauthorized model access

  • Implement

    AI guardrails

    such as input/output validation, PII masking, and content filtering
  • Deploy and manage

    LLM firewall / AI security tools

    (Giskard, AI Shield, Arthur Shield, or similar)
  • Secure

    RAG pipelines, fine-tuning workflows, and agentic AI architectures

  • Protect AI workloads on

    Azure AI Foundry and Azure OpenAI

  • Govern usage of

    Hugging Face models/datasets

    and

    Microsoft Copilot

  • Integrate AI security controls into

    CI/CD and MLOps pipelines

  • Support

    AI risk assessments, audits, and regulatory compliance

Required Technical Skills

  • Strong understanding of

    LLMs, ML, NLP, and deep learning

  • Knowledge of

    OWASP Top 10 for LLMs

    and AI threat models
  • Experience with

    Azure AI platforms

    , APIs, IAM, encryption, and logging
  • Hands-on experience with

    AI security / LLM firewall tools

  • Solid foundation in

    application security, cloud security, and DevSecOps

Qualifications

  • Bachelor’s or master’s degree in computer science

    , Information Security, AI/ML, or related field

  • 6–10 years

    of experience in

    Security Engineering, Cloud Security, or AI/ML Security

Nice to Have

  • Experience in

    BFSI or regulated environments

  • Exposure to

    Responsible AI, AI governance, or adversarial ML


Roles and Responsibilities

Key Responsibilities

  • Secure

    LLMs, ML models, NLP systems, and deep learning pipelines

  • Identify and mitigate AI risks including

    prompt injection, data leakage, model poisoning, hallucination misuse, and unauthorized model access

  • Implement

    AI guardrails

    such as input/output validation, PII masking, and content filtering
  • Deploy and manage

    LLM firewall / AI security tools

    (Giskard, AI Shield, Arthur Shield, or similar)
  • Secure

    RAG pipelines, fine-tuning workflows, and agentic AI architectures

  • Protect AI workloads on

    Azure AI Foundry and Azure OpenAI

  • Govern usage of

    Hugging Face models/datasets

    and

    Microsoft Copilot

  • Integrate AI security controls into

    CI/CD and MLOps pipelines

  • Support

    AI risk assessments, audits, and regulatory compliance

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