Senior AI Security Engineer

Company: Quarks Technosoft

Location: Noida, Pune, Bengaluru

Type: Full-time

Posted: 2026-10-29

About this role

## Job highlights

  • Bachelor s degree in any discipline,or equivalent professional experience
  • Demonstrated experience red-teaming AI systems against prompt injection,jailbreaks,excessive agency and model abuse - candidates should be able to walk through specific findings they produced. -
  • Minimum 1-2 years of hands-on work securing or testing production generative AI,LLM or agentic systems. -

">Senior AI Security Engineer

7-10 Years Bengaluru, Pune, Noida

  • AI Security

Essential qualifications and experience

  • Bachelor s degree in any discipline, or equivalent professional experience; demonstrated engineering practice is the primary criterion.
  • Minimum 6 years in security engineering, application security, offensive security, detection engineering or cloud security.
  • Minimum 1-2 years of hands-on work securing or testing production generative AI, LLM or agentic systems.
  • Demonstrated experience red-teaming AI systems against prompt injection, jailbreaks, excessive agency and model abuse - candidates should be able to walk through specific findings they produced.
  • Strong Python, with the ability to build test harnesses, automation and tooling to a production standard.
  • Solid cloud security engineering experience on a major hyperscaler; Azure preferred.
  • Practical understanding of LLM application architecture: embeddings, vector databases, RAG, agent frameworks, tool and function calling, and the MCP-style integration pattern.
  • Working knowledge of OWASP Top 10 for LLM Applications, OWASP agentic security guidance and MITRE ATLAS.
  • CI/CD and infrastructure-as-code fluency; comfortable embedding security checks into delivery pipelines.
  • Practical use of current AI development tooling - agent-building platforms, AI-assisted coding environments and locally hosted models - to build tooling and evaluation harnesses at speed.
  • Clear written reporting - findings must be reproducible and actionable by the receiving team.



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