AI Security Engineer / Architect

Job Summary

Transforming the Future of Enterprise Planning

At o9, our mission is to be the Most Value-Creating Platform for enterprises by transforming decision-making through our AI-first approach. By integrating siloed planning capabilities and capturing millions-even billions-in value leakage, we help businesses plan smarter and faster.

This not only enhances operational efficiency but also reduces waste, leading to better outcomes for both businesses and the planet. Global leaders like Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains.

Role: AI Offensive Security Researcher - Red Team, VAPT Agentic Security

Location: Bangalore, Hybrid

About the role...

We are looking for a AI offensive Security researcher / Senior AI Security Engineer/Architect with MLSecOps experience to lead the next generation of AI-native security at o9.

You will own two parallel missions: securing o9's GenAI platform and agentic AI ecosystem from emerging threats, and building AI/ML-driven capabilities that transform how our security operations detect, predict, and respond to adversarial activity across 500+ customer environments.

Our security platform ingests 22 billion events per month across 176,000+ hosts, 266 Kubernetes clusters, and 3,042 cloud accounts. The intelligence hidden in that telemetry remains largely unmined. Simultaneously, o9's GenAI platform is scaling rapidly - production AI agents, RAG pipelines, MCP tool integrations, and autonomous planning workflows that introduce a fundamentally new class of security risk. This role exists to address both.

What you'll do:

• Design and execute AI-specific VAPT engagements - prompt injection chains, RAG pipeline poisoning, agent identity spoofing, and tool-layer exploitation across MCP and A2A boundaries
• Lead structured AI red team exercises and scenario-based tabletops, delivering CVSS - scored, MITRE ATLAS mapped findings with actionable remediation guidance
• Build and maintain AI security automation tooling: prompt fuzzing harnesses, guardrail regression test suites, and detection rule generators fed by red team TTP libraries
• Contribute to threat modeling for agentic systems - mapping trust boundaries, privilege escalation paths, and blast radius across autonomous agent clusters
• Feed red team findings back into detection engineering as quality inputs, closing the loop between offensive discovery and SOC coverage gaps

What you'll have:

• 4-12+ years in application security, AI/ML security, or offensive security research with at least one demonstrable AI-specific assessment or published finding
• Hands-on offensive depth across LLM attack surfaces: jailbreaks, multi-modal injection, agentic control gaps, and indirect prompt injection
• Working knowledge of MLOps pipelines, ML engineering concepts, or cloud security as contextual grounding
• CFP submissions, responsible disclosure history, or published AI security research is a strong differentiator

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.