AI Security & Information Protection Analyst – Agentic AI

Vibehackers; Chennai District; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Vibehackers seeks an AI Security & Information Protection Analyst focused on agentic AI. You will assess risks from LLM agents, RAG flows, and tool-calling, implementing controls to prevent prompt injection, data exfiltration, and model abuse.

You will design guardrails, tune DLP across platforms, investigate incidents, and contribute to vendor risk assessments, ensuring safe business use of AI.

Qualifications

• Foundational knowledge of agentic AI, RAG, prompt injection, and DLP policies.
• Experience with at least one enterprise DLP/CASB/SSE platform or SIEM/EDR.
• Strong analytical skills and ability to document and communicate findings.
• Exposure to LLM ecosystems, vector stores, and security guidance.
• Familiarity with Python, logs/JSON, and standards like NIST AI RMF.

Responsibilities

• Assess agentic AI patterns including LLM agents, tool calling, orchestration, and RAG for security and data-leakage risks.
• Support and design AI security guardrails, secure configurations, role/data scoping, policies and reference architectures.
• Administer and tune DLP controls across endpoints, email, collaboration platforms, cloud, and SaaS; monitor and remediate alerts with data owners.
• Detect unsanctioned AI applications, risky plugins/extensions, shadow AI, and risky data uploads.
• Support investigations using agent logs and prompt histories; develop playbooks and AI security KPIs/KRIs.
• Contribute to AI policy, vendor due diligence, and third-party risk assessments.

Skills

DLP concepts

Threat assessment

Incident response

Governance & compliance

Stakeholder communication

Tools

SIEM/EDR monitoring

SaaS governance tooling

DLP platforms

Policy development

Job description

AI Security & Information Protection Analyst – Agentic AI

Focused on securing agentic LLMs and RAG flows; hands-on work with prompt-injection patterns, agent frameworks, and AI security tooling.

About the Role

Responsible for assessing and mitigating security and information protection risks introduced by agentic AI (LLM agents, RAG, tool-calling and orchestration). Implement and tune DLP controls, investigate incidents, produce secure AI guidance, and conduct third-party AI vendor risk assessments to enable safe business use of AI.

Job Description

Role

AI Security & Information Protection Analyst (Agentic AI focus) responsible for assessing agentic AI use cases and implementing controls to prevent prompt injection, data exfiltration, model abuse, unsafe tool invocation, and supply-chain risks.

Key Responsibilities

• Assess agentic AI patterns including LLM agents, tool/function calling, orchestration, and RAG for security and data-leakage risks.
• Support and design AI security guardrails, secure configurations, role/data scoping, allow/deny policies, reference architectures, and usage guidance.
• Administer and tune DLP controls across endpoints, email, collaboration platforms, cloud, and SaaS; monitor, triage, escalated, and remediate alerts with data owners and legal/privacy teams.
• Detect unsanctioned AI applications, risky plugins/extensions, shadow AI, and risky data uploads.
• Support investigations using agent logs, tool-call traces, and prompt/response histories; develop playbooks and AI security KPIs/KRIs.
• Contribute to AI policy, training, third-party due diligence, and vendor/SaaS assessments covering residency, retention, training-data controls, auditability, and transparency.

Requirements

• Foundational knowledge of agentic AI, RAG, prompt injection, leakage pathways, DLP policies/classifiers/incident workflows, IAM, least privilege, network and SaaS security.
• Experience with at least one enterprise DLP/CASB/SSE platform, SIEM/EDR/cloud-security monitoring, or SaaS governance.
• Strong analytical skills, documentation, stakeholder communication, adaptability, and a learning mindset.
• Exposure to LLM ecosystems, agent frameworks, vector stores, model gateways, prompt-injection and exfiltration patterns.
• Familiarity with Python or PowerShell, logs/JSON, and standards/guidance such as NIST AI RMF, ISO/IEC 23894, OWASP LLM guidance, or MITRE ATLAS.

Success in the First Six Months

• Baseline sanctioned and unsanctioned AI usage and improve AI-focused DLP precision.
• Publish secure AI guidance and implement initial detections/playbooks for prompt injection, risky tools, and abnormal data movement.
• Complete at least one AI vendor or solution risk assessment.
• OSP contractor: six months with possible extension.
• Hybrid/remote per terms; limited on-call or incident-support windows may apply.
• Candidates should be comfortable with ambiguity, incremental improvement, and pragmatic, hands-on work to protect sensitive data while enabling business value.

LLM agents LLM ecosystems RAG agent frameworks tool/function calling vector stores model gateways DLP CASB SSE SIEM EDR cloud-security monitoring SaaS governance IAM Python PowerShell JSON EDM/IDM fingerprints NIST AI RMF ISO/IEC 23894 OWASP LLM guidance MITRE ATLAS

Skills

Analytical thinking Documentation Stakeholder communication Adaptability Learning mindset Incident response Investigations Risk assessment Policy development Vendor/SaaS assessments

Experience Level

Mid

Employment Type

Full Time, Permanent

• Hybrid/Remote (per terms)
• Limited on-call / incident-support windows