Sec Ops Architect

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, Pepsi Co, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains.

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. Global leaders like Google, Pepsi Co, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains.

We are looking for a Senior AI Security & MLSecOps Architect to lead the next generation of AI-native security  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.

Own the security architecture for o9’s GenAI platform — ensuring every AI agent, model, and integration is governed, auditable, and stoppable.

• AI Agent Security Architecture: Design and enforce agent identity controls, permission scoping, and behavioural baselining for all production AI agents. Build UEBA-style models that detect when an agent deviates from learned tool-call patterns, data-access scope, or egress destinations — triggering automated containment via kill-switch controls.
• AI SBOM & Model
  
  Risk Management:
  
  Architect the AI Bill of Materials (AIBOM/SBOM) pipeline — model provenance verification, hash integrity, dependency scanning, and supply chain trust for every LLM, embedding model, and agent deployed to production. Ensure no model reaches production without a signed inventory entry.
• RAG & Prompt Security: Design security controls for retrieval-augmented generation pipelines — source allow listing, tenant isolation, PII scrubbing, indirect prompt injection detection, and embedding anomaly monitoring. Secure the retrieval boundary as the highest-risk component in the AI stack.
• Cross-System AI Integration Security: Define security review gates for AI integrations with enterprise systems (ticketing, Dev Ops, observability, MCP servers). Enforce token governance, credential rotation, blast-radius modelling, and data classification for every cross-system data flow.
• AI Governance & Compliance: Align AI security controls to ISO 42001, NIST AI RMF, MITRE ATLAS, and OWASP Top 10 for LLM Applications. Maintain audit trails for every model decision. Support EU AI Act and DPDPA compliance evidence generation.

Build ML models and autonomous agents that…