Senior Domain Manager Cyber Security

Pune - India

Monthly Salary: Not Disclosed

Posted on: 20 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Purpose	Identify and exploit vulnerabilities in AI models and systems through realistic adversarial simulations to prevent exploitation by malicious actors. Evaluate models for security weaknesses and risks like Supply chain AIBOM vulnerabilities across GenAI & Agentic platform. Hands on experience on critical attack techniques including prompt injection jailbreaking data poisoning model inversion and good understanding on OWASP LLM Top 10 OWASP Agentic Top 10 MITRE ATLAS framework. Plan and conduct targeted red team engagements across large language models generative AI applications and supporting ML infrastructure. Produce detailed actionable reports with clear attack reproductions impact assessments and recommended hardening measures. Good understanding on Guardrail implementation Rule engine Policy configuration and AI Runtime security. Safeguard live AI inference environments and deployed models against active runtime threats including model extraction evasion backdoor activation and prompt-based attacks. Implement layered runtime defenses such as input/output sanitization anomaly detection rate limiting and content scanning tailored to AI workloads. Perform threat modeling and risk analysis tailored to agentic architectures focusing on risks such as goal misalignment tool misuse and privilege escalation. Work closely with MLOps platform and SRE teams to embed runtime protection practices into deployment pipelines and operational processes. Lead incident response for AI-specific security events performing root-cause analysis containment and remediation with minimal service disruption. Assess Third Party Partner vulnerabilities and security risk Create and maintain specialized tooling test harnesses and automation to enable efficient repeatable adversarial security testing for AI systems. Regular cadence with AI Development team for secure design suggest architectural reviews. Connect with AI
Duties and Responsibilities	A-Minimum required Accountabilities for this role Engineering / Computer Graduate with 4-6 years of Information / Cyber Security Experience and minimum 1-2 years of hands-on experience on AI Red Teaming AI Guardrails implementation will be preferred. B-Additional Accountabilities pertaining to the role AI securityrelated certifications (Good to Have)
Key Decisions / Dimensions	Involvement in Activity calendar planning and execution of AI applications Preparation of testcases for AI Red Teaming and highlight the risk imposing of the vulnerabilities
Major Challenges	AI Red Teaming understanding execution reporting & timely closure from stakeholders Change management and AI sign off with in defined TAT
Required Qualifications and Experience	a)Qualifications Post-Graduates with relevant security experience of 4-6years (also graduates with experience of 6-8 years may apply) b)Work Experience Engineering / Computer Graduate with 4-6 years of Information / Cyber Security Experience AI securityrelated certifications (Good to Have) Understanding of OWASP LLM Top 10 OWASP Agentic Top 10 MITRE ATLAS framework. Common AI-specific threats: Prompt injection (direct & indirect) Model poisoning & data poisoning Model theft / extraction Hallucination abuse & unsafe outputs Threat modeling for AI systems (LLMs RAG agents) Strong understanding of application security (OWASP Top 10 API Security Top 10) Secure SDLC practices (design reviews threat modelling secure coding)

Required Experience:

Manager

Job PurposeIdentify and exploit vulnerabilities in AI models and systems through realistic adversarial simulations to prevent exploitation by malicious actors.Evaluate models for security weaknesses and risks like Supply chain AIBOM vulnerabilities across GenAI & Agentic platform. Hands on experienc...

Job Purpose	Identify and exploit vulnerabilities in AI models and systems through realistic adversarial simulations to prevent exploitation by malicious actors. Evaluate models for security weaknesses and risks like Supply chain AIBOM vulnerabilities across GenAI & Agentic platform. Hands on experience on critical attack techniques including prompt injection jailbreaking data poisoning model inversion and good understanding on OWASP LLM Top 10 OWASP Agentic Top 10 MITRE ATLAS framework. Plan and conduct targeted red team engagements across large language models generative AI applications and supporting ML infrastructure. Produce detailed actionable reports with clear attack reproductions impact assessments and recommended hardening measures. Good understanding on Guardrail implementation Rule engine Policy configuration and AI Runtime security. Safeguard live AI inference environments and deployed models against active runtime threats including model extraction evasion backdoor activation and prompt-based attacks. Implement layered runtime defenses such as input/output sanitization anomaly detection rate limiting and content scanning tailored to AI workloads. Perform threat modeling and risk analysis tailored to agentic architectures focusing on risks such as goal misalignment tool misuse and privilege escalation. Work closely with MLOps platform and SRE teams to embed runtime protection practices into deployment pipelines and operational processes. Lead incident response for AI-specific security events performing root-cause analysis containment and remediation with minimal service disruption. Assess Third Party Partner vulnerabilities and security risk Create and maintain specialized tooling test harnesses and automation to enable efficient repeatable adversarial security testing for AI systems. Regular cadence with AI Development team for secure design suggest architectural reviews. Connect with AI
Duties and Responsibilities	A-Minimum required Accountabilities for this role Engineering / Computer Graduate with 4-6 years of Information / Cyber Security Experience and minimum 1-2 years of hands-on experience on AI Red Teaming AI Guardrails implementation will be preferred. B-Additional Accountabilities pertaining to the role AI securityrelated certifications (Good to Have)
Key Decisions / Dimensions	Involvement in Activity calendar planning and execution of AI applications Preparation of testcases for AI Red Teaming and highlight the risk imposing of the vulnerabilities
Major Challenges	AI Red Teaming understanding execution reporting & timely closure from stakeholders Change management and AI sign off with in defined TAT
Required Qualifications and Experience	a)Qualifications Post-Graduates with relevant security experience of 4-6years (also graduates with experience of 6-8 years may apply) b)Work Experience Engineering / Computer Graduate with 4-6 years of Information / Cyber Security Experience AI securityrelated certifications (Good to Have) Understanding of OWASP LLM Top 10 OWASP Agentic Top 10 MITRE ATLAS framework. Common AI-specific threats: Prompt injection (direct & indirect) Model poisoning & data poisoning Model theft / extraction Hallucination abuse & unsafe outputs Threat modeling for AI systems (LLMs RAG agents) Strong understanding of application security (OWASP Top 10 API Security Top 10) Secure SDLC practices (design reviews threat modelling secure coding)

Required Experience:

Manager

Key Skills

IT Experience
ISO 27001
Splunk
System Security Plans
Network security
HTTPS
PCI
gRPC
NIST Standards
Information Security
Encryption
ISO 27002

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