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AI Security Engineer

Systems Limited · Pendjab

Senior 🇬🇧 English
LLM security prompt engineering RAG embeddings vector search AI agents Azure AWS GCP SAST DAST SIEM vulnerability scanning security monitoring data privacy compliance responsible AI governance AI security frameworks LLM red teaming AI guardrails content safety prompt filtering output validation OWASP Top 10 for LLM Applications

Job description

About the role

Systems Ltd is seeking an experienced AI Security Engineer to protect AI‑powered applications, large language models, and enterprise AI platforms. The role focuses on identifying and mitigating AI‑specific threats such as prompt injection, jailbreaks, data leakage, and unsafe model outputs.

Key responsibilities

  • Design and implement security controls for AI applications, LLM integrations, AI agents, and RAG‑based systems.
  • Identify, assess, and mitigate AI‑specific threats including prompt injection, jailbreaks, data exfiltration, hallucination risks, and insecure tool usage.
  • Secure prompt workflows, system prompts, agent instructions, retrieval pipelines, and AI orchestration layers.
  • Conduct threat modeling, red‑team exercises, and security audits for AI solutions and enterprise assistants.
  • Define and enforce AI security governance, responsible AI controls, and compliance best practices.
  • Collaborate with engineering, cloud, and product teams to secure AI APIs, cloud deployments, access controls, and production platforms.

Required profile

  • 6‑9 years of hands‑on experience securing AI applications, LLMs, RAG pipelines, and AI agents.
  • Strong background in cloud environments (Azure, AWS, or GCP) and security tooling (SAST, DAST, SIEM, vulnerability scanning, security monitoring).
  • Familiarity with data privacy, compliance, and responsible AI practices.
  • Relevant certifications such as CISSP, CEH, Security+, or cloud security certifications.
  • Experience in regulated sectors such as telecom, fintech, or enterprise environments.

Required skills

  • LLM security, prompt engineering, RAG, embeddings, vector search.
  • AI agents, tool‑calling systems, enterprise chatbot platforms.
  • Azure, AWS, GCP AI services and API deployments.
  • SAST, DAST, SIEM, vulnerability scanning, security monitoring.
  • Data privacy, compliance, responsible AI governance.
  • AI security frameworks, LLM red‑teaming, AI guardrails, content safety, prompt filtering, output validation.
  • OWASP Top 10 for LLM Applications or similar AI security guidance.

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Published 1 month ago

Expires 1 week from now

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Systems Limited

Pendjab